The combination of generative AI (GenAI) and the Internet of Things (IoT) holds the potential to reshape the future of technology and drive unprecedented innovation.

GenAI promises to revolutionize the IoT ecosystem by enhancing security, personalization, anomaly detection, on-device machine learning, and network management.

As these areas continue to evolve, businesses and individuals are ready to benefit from the innovative applications of GenAI. In this article, we’ll explore the many ways GenAI is beginning to transform the IoT landscape and examine the future possibilities of this powerful alliance.

Creating Synthetic Data for Machine Learning

One of the main challenges in developing machine learning models for IoT devices revolves around collecting and labeling massive amounts of data. However, GenAI solves this problem by creating synthetic data to train these models.

This synthetic data can be used to simulate a variety of scenarios, including machine failures. For example, a manufacturing company can use GenAI to create synthetic data that represents different machine failure scenarios. The company can then use this data to train machine learning models to anticipate potential problems in advance, enabling predictive maintenance.

Crafting Personalized Experiences

GenAI enables IoT devices to deliver personalized experiences to users by leveraging its ability to generate new and original content. Smart home systems can use GenAI algorithms to create personalized lighting and temperature settings for individual users, enhancing comfort and convenience.

And wearable devices can use GenAI to offer tailored workout recommendations based on an individual’s fitness goals and preferences. By leveraging user data from surveys, interactions, and sensor inputs, GenAI can create unique and personalized experiences tailored to the specific needs of each user.

Improving Anomaly Detection

Anomaly detection is key to ensuring the reliability and security of IoT networks. GenAI has the ability to greatly improve anomaly detection by creating synthetic data that accurately simulates normal operating conditions. By training machine learning models on this synthetic data, IoT devices can effectively identify and flag irregular events in real time.

For example, an operator of a power grid can use GenAI to generate synthetic data that mirrors typical power consumption patterns. The power grid operator can then use that data to train a machine learning model that can detect sudden spikes or irregularities in power consumption, enabling the operator to take proactive measures to prevent potential failures or security breaches.

Enabling On-Device Machine Learning

The combination of GenAI and IoT introduces exciting prospects for on-device machine learning. GenAI tackles the issue of limited computing resources in IoT devices by creating smaller and more effective machine learning models.

Anomaly detection models, for instance, can be optimized and implemented directly on IoT devices, enabling real-time analysis and decision-making without depending on cloud resources. This reduces latency as well as strengthens data privacy and security by reducing the need to send data to external servers.

Automating Network Management

Managing large-scale IoT networks requires intelligent automation. GenAI can be instrumental in automating different areas of network management, including configuring devices and optimizing network traffic. With its generative abilities, GenAI can automatically set up new devices as they join the network, simplifying the onboarding process.

Additionally, GenAI can enhance network traffic by intelligently directing data through the most efficient routes, reducing latency and maximizing the use of available bandwidth. This automation lessens the workload of network administrators and boosts the performance and efficiency of the network.

Potential Future IoT Applications

As GenAI continues to evolve, the possibilities for its integration with IoT are endless. Some potential applications include:

Creating New Types of IoT Devices: GenAI can facilitate the development of innovative IoT devices, such as smart assistants with natural language processing capabilities. These devices will be able to understand and respond to human commands and queries, revolutionizing the way we interact with technology.

Enhancing User Interactions: GenAI can enable new ways to interact with IoT devices, including gesture recognition and voice commands. This will make technology more intuitive and accessible, improving the user experience.

Improving Security and Reliability: GenAI can assist in developing advanced security measures for IoT networks, effectively mitigating cyber threats and ensuring data privacy. By generating synthetic data to train anomaly detection models, GenAI can help identify and prevent security breaches in real-time.

Democratizing IoT Access: GenAI has the potential to help bridge the digital divide by making IoT devices more affordable and accessible and allow more people to benefit from the advantages of intelligent connectivity. Democratizing IoT access will allow businesses and individuals to take advantage of IoT technologies for various applications and industries.

Conclusion

The integration of GenAI and IoT has the potential to totally transform how we interact with and benefit from intelligent connectivity. By leveraging GenAI, businesses and individuals can unlock a wide array of applications, ranging from improved anomaly detection and personalized experiences to on-device machine learning and network management automation.

As the field continues to evolve, it’s vital that we embrace the possibilities presented by GenAI and explore its potential to transform IoT. The future of GenAI in IoT is bright, promising a new era of intelligent connectivity and unprecedented opportunities for innovation.

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AI will not take all jobs nor end civilization. But it will help businesses make better decisions.

Artificial intelligence (AI) is everywhere. And stories are rampant about its promise and its threat. Will AI’s potential be realized in the year ahead?

SAS, the leader in AI and analytics, asked executives and experts across the company to predict trends and key business and technology developments in AI for 2024.

Below are some of the predictions they shared.

Generative AI will augment (not replace) a comprehensive AI strategy

“Generative AI technology does a lot of things, but it can’t do everything. In 2024, organizations will pivot from viewing generative AI as a stand-alone technology to integrating it as a complement to industry-specific AI strategies. In banking, simulated data for stress testing and scenario analysis will help predict risks and prevent losses. In health care, that means the generation of individualized treatment plans. In manufacturing, generative AI can simulate production to identify improvements in quality, reliability, maintenance, energy efficiency and yield.” – Bryan Harris, Chief Technology Officer, SAS
[Note: Earlier this year, SAS committed $1 billion to AI-powered industry solutions.]

AI will create jobs

“In 2023, there was a lot of worry about the jobs that AI might eliminate. The conversation in 2024 will focus instead on the jobs AI will create. An obvious example is prompt engineering, which links a model’s potential with its real-world application. AI helps workers at all skill levels and roles to be more effective and efficient. And while new AI technologies in 2024 and beyond may cause some short-term disruptions in the job market, they will spark many new jobs and new roles that will help drive economic growth.” – Udo Sglavo, Vice President of Advanced Analytics, SAS

AI will enhance responsible marketing

“As marketers we must consciously practice responsible marketing. Facets of this are awareness of the fallibility of AI and alertness to possible bias creeping in. While AI offers the promise of enhanced marketing and advertising programs, we know that biased data and models beget biased results. In SAS Marketing, we are implementing model cards that are like an ingredient list, but for AI. Whether you create or apply AI, you are responsible for its impact. That’s why all marketers, regardless of technical know-how, can review the model cards, validate that their algorithms are effective and fair, and adjust as needed.” – Jennifer Chase, Chief Marketing Officer, SAS

Financial firms will embrace AI amid a Dark Age of Fraud

“Even as consumers signal increased fraud vigilance, generative AI and deepfake technology are helping fraudsters hone their multitrillion-dollar craft. Phishing messages are more polished. Imitation websites look stunningly legitimate. A crook can clone a voice with a few seconds of audio using simple online tools. We are entering the Dark Age of Fraud, where banks and credit unions will scramble to make up for lost time in AI adoption – incentivized, no doubt, by regulatory shifts forcing financial firms to assume greater liability for soaring APP [authorized push payment] scams and other frauds.” – Stu Bradley, Senior Vice President of Risk, Fraud and Compliance Solutions, SAS

Shadow AI will challenge CIOs

“CIOs have struggled with ‘shadow IT’ in the past and will now confront ‘shadow AI’ – solutions used by or developed within an organization without official sanction or monitoring by IT. Well-intentioned employees will continue to use generative AI tools to increase productivity. And CIOs will wrestle daily with how much to embrace these generative AI tools and what guardrails should be put in place to safeguard their organizations from associated risks.” – Jay Upchurch, Chief Information Officer, SAS

Multimodal AI and AI simulation will reach new frontiers

“The integration of text, images and audio into a single model is the next frontier of generative AI. Known as multimodal AI, it can process a diverse range of inputs simultaneously, enabling more context-aware applications for effective decision making. An example of this will be the generation of 3D objects, environments and spatial data. This will have applications in augmented reality [AR], virtual reality [VR], and the simulation of complex physical systems such as digital twins.” – Marinela Profi, AI/Generative AI Strategy Advisor, SAS

Digital-twin adoption will accelerate

“Technologies like AI and IoT [Internet of Things] analytics drive important sectors of the economy, including manufacturing, energy and government. Workers on the factory floor and in the executive suite use these technologies to transform huge volumes of data into better, faster decisions. In 2024, the adoption of AI and IoT analytics will accelerate through broader use of digital-twin technologies, which analyze real-time sensor and operational data and create duplicates of complex systems like factories, smart cities and energy grids. With digital twins, organizations can optimize operations, improve product quality, enhance safety, increase reliability and reduce emissions.” – Jason Mann, Vice President of IoT, SAS

Insurers will confront climate risk, aided by AI

“After decades of anticipation, climate change has transformed from speculative menace to genuine threat. Global insured losses from natural disasters surpassed $130 billion in 2022, and insurers worldwide are feeling the squeeze. US insurers, for example, are under scrutiny for raising premiums and withdrawing from hard-hit states like California and Florida, leaving tens of millions of consumers in the lurch. To survive this crisis, insurers will increasingly adopt AI to tap the potential of their immense data stores to shore up liquidity and be competitive. Beyond the gains they realize in dynamic premium pricing and risk assessment, AI will help them automate and enhance claims processing, fraud detection, customer service and more.” – Troy Haines, Senior Vice President of Risk Research and Quantitative Solutions, SAS

AI importance will grow in government

“The workforce implications of AI will start being felt in government. Governments have a hard time attracting and retaining AI talent since experts command such high salaries, however, they will aggressively recruit for expertise to support regulatory actions. And like enterprises, governments will also increasingly turn to AI and analytics to boost productivity, automate menial tasks and mitigate that talent shortage.” – Reggie Townsend, Vice President of the SAS Data Ethics Practice

Generative AI will bolster patient care

“To advance health and improve patient and member experiences, organizations will further develop generative AI-powered tools in 2024 for personalized medicine, such as the creation of patient-specific avatars for use in clinical trials and the generation of individualized treatment plans. Additionally, we will see the emergence of generative AI-based systems for clinical decision support, delivering real-time guidance to payers, providers and pharmaceutical organizations.” – Steve Kearney, Global Medical Director, SAS

Deliberate AI deployment will make or break insurers

“In 2024, one of the top 100 global insurers will go out of business as a consequence of deploying generative AI too quickly. Right now, insurers are rolling out autonomous systems at breakneck speed with no tailoring to their business models. They’re hoping that using AI to crunch through claims quickly will offset the last few years of poor business results. But after 2023’s layoffs, remaining staff will be spread too thin to enact the necessary oversight to deploy AI ethically and at scale. The myth of AI as a cure-all will trigger tens of thousands of faulty business decisions that will lead to a corporate collapse, which may irreparably damage consumer and regulator trust.” – Franklin Manchester, Global Insurance Strategic Advisor, SAS

Public health will get an AI boost from academia

“Public health is achieving technologic modernization at an unprecedented rate. Whether overdoses or flu surveillance, using data to anticipate public health interventions is essential. Forecasting and modeling are rapidly becoming the cornerstone of public health work, but government needs help. Enter academia. We will see an increase in academic researchers carrying out AI-driven modeling and forecasting on behalf of government. It is clear after COVID-19 that the protection of our population will require exceptional technology and collaboration.” – Dr. Meghan Schaeffer, National Public Health Advisor and Epidemiologist, SAS

The post AI reality vs. myth: Twelve predictions from SAS for 2024 appeared first on IoT Business News.

News highlights:

• New Arm Cortex-M52 is the smallest, most area- and cost-efficient processor enabled with Arm Helium technology, delivering enhanced AI capabilities for lower cost IoT devices
• Provides the flexibility to scale across a range of performance points and configurations, delivering DSP capabilities without a separate unit to save on area and cost
• Simplified development flows bring AI within reach on a single toolchain and single proven architecture

Generative Artificial Intelligence (AI) and Large Language Models (LLMs) are grabbing headlines, but many don’t realize how much AI is already deployed in embedded devices and impacting applications across our homes, cities and in industry – this is referred to as the Artificial Intelligence of Things (AIoT), and it’s being built on Arm. AI is critical to understanding data and enabling more seamless interactions between the physical and digital world. As this technology advances, on-device intelligence is being deployed in smaller, more cost-sensitive and often battery powered devices at the lowest cost points, with greater privacy and reliability due to less reliance on the cloud.

As AI-enabled IoT shipments continue to increase, our partners need access to more ML (Machine Learning) capabilities and simpler development flows, giving them the agility to innovate and scale quickly. To address these requirements, today we are announcing the Arm Cortex-M52, designed for AIoT applications that require a boost in digital signal processing (DSP) and ML performance without the cost overhead of dedicated DSP and ML accelerators. Cortex-M52 will unlock the potential for delivering ML on embedded computing solutions at lower price points than is possible today.

Bringing AI capabilities to a broader range of IoT devices

The Cortex-M52 includes Arm Helium technology, providing a significant performance uplift in DSP and ML applications for small, low power embedded devices, making it possible to deploy more compute intensive ML inference algorithms in endpoints without a dedicated NPU. Helium technology has already been implemented successfully in products at the far edge of the network, but the Cortex-M52 now enables Arm partners to take this capability into lower cost more power constrained devices.

By extending Helium technology into a new class of Cortex-M, Arm is delivering a step change in matrix and DSP compute on microcontrollers for smaller embedded devices. The Cortex-M52 provides a simplified migration path from the Cortex-M33 and Cortex-M4, addressing a wide range of AIoT applications to enable richer UI, voice and vision experiences, such as automotive and industrial control, predictive maintenance, and wearable sensor fusion. Cortex-M52 delivers the flexibility needed to scale across a range of performance points and configurations, providing DSP capabilities without a separate processing unit, saving on silicon area and cost.

Providing optimal performance and cost choice with robust safety and security

Cortex-M52 extends the Armv8.1-M Cortex-M line-up (which includes the Cortex-M55 and Cortex-M85) to a new efficiency point, a critical milestone in bringing ML capabilities to microcontrollers. It provides the lowest area and power implementation of any Helium-enabled Cortex-M, offering choice to silicon partners looking to trade-off performance and cost. Developers can benefit from an uplift in bothML and DSP performance, with up to 5.6x performance uplift for ML and up to 2.7x performance uplift for digital signal processing compared to previous Cortex-M generations.

Security remains critical in devices, especially when shipping at large scale, and Cortex-M52 implements the latest security extensions for Armv8.1-M, including PACBTI and Arm TrustZone technology, which offers enhanced software threat mitigation. In addition, Cortex-M52 will accelerate the route to PSA Certified Level 2 silicon, enabling the next generation of PSA Certified devices. The latest Armv8.1-M cores (including Cortex-M55 and Cortex-M85) also offer enhanced functional safety features that are crucial in many automotive and industrial control applications. The Cortex-M52 delivers these extended safety packages and features to help partners reach FuSa certification faster and more easily, compared to previous generation Cortex-Ms being deployed in these applications.

Simplifying AI development for the smallest endpoint devices

Traditional embedded developers grapple with the mathematical, data analysis, toolchain expertise and programming skills required for AI. Developer enablement is critical if we are to see an increase in AIoT shipments, and with the Cortex-M52 we’re delivering the critical features and capabilities required in a modern development flow today.

Historically, to achieve the ML and DSP performance Cortex-M52 delivers would have required the combination of a CPU, a DSP and an NPU, meaning that once the hardware is built, developers would need to write, debug and tune code for chips with three separate tool chains, three compilers, three debuggers, and so on. Now, we are bringing AI within reach on a single toolchain and single proven architecture with the industry-standard, user-friendly Arm Cortex-M portfolio. This ensures a unified development flow for traditional, DSP and ML workloads – while specific integration and optimizations for leading machine learning frameworks will ensure that developers have a seamless experience and get the best performance from any Cortex-M.

Cortex-M52 is fully software compatible with Cortex-M55 and Cortex-M85, enabling developers to benefit from and leverage the growing software and tools ecosystem around Helium, as well as free software libraries and an extensive knowledge base from our partner ecosystem. To help streamline and accelerate the IoT and embedded development process, Cortex-M52 will also be available on Arm Virtual Hardware, our cloud-based offering that enables software development in advance of silicon.

Deploying AI across the full spectrum of AIoT use cases, built on Arm

The AIoT runs on Arm and together with our partners, we identified a need to bring DSP and ML compute performance to low power embedded applications at a better cost and accessibility point for the market. The Cortex-M52 CPU delivers higher levels of AI inference performance on the smallest devices, enabling the industry to scale IoT device deployments even further.

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Fibocom unveils a high-performance, multi-mode LTE smart module SC228 to drive digital transformation across AIoT industries. Empowered by the Qualcomm Snapdragon® SM6225 chip, the module delivers superior CPU processing performance and excellent power efficiency backed by the features of an Octa-core (4*A73 2.4G + 4*A53 1.9G) processor and high-level graphics processor.

Fibocom, a global leading provider of IoT (Internet of Things) wireless solutions and wireless communication modules, announces the release of a new LTE smart module SC228 for the acceleration of digital transformation in smart retailing, smart wearable camera, Industrial IoT, In-vehicle infotainment market.

Integrated with a 6nm processor, the module utilizes the powerful CPU and GPU to deliver superior multimedia performance while conserving power. Compatible with frequency bands worldwide, the module also supports Bluetooth and dual-band Wi-Fi for short-distance wireless communication.

The integration of AI and IoT is reshaping the way that decision-makers from various industries operate and respond to real-time information. The highly integrated smart module SC228 is capable of offering a comprehensive solution for industry customers to improve product performance and facilitate the decision-making process. Equipped with a powerful CPU, SC228 can support the smooth running of AI algorithms, which ensures the terminals realize a bunch of functionalities such as facial recognition, HMI (Human-machine Interaction), etc. In terms of multimedia processing, the SC228 is integrated with a low-power island DSP (Digital Signal Processors) for sensors and audio, furthermore, it also supports multi-camera input and output with up to three of them working simultaneously. To cater to diverse IoT application scenarios, the SC228 is designed with rich interfaces including MIPI/ USB/ UART/ SPI/ I2C to help customers develop the terminals flexibly.

In software design, the SC228 is preset with an upgradable Android 14 operating system in cope with the ever-evolving software innovations, which can help our customers quickly meet the requirements for GMS (Google Mobile Service) certification and continuous development for long lifecycle terminals. Notably, the premium smart module is also built-in with GNSS for fast and accurate positioning for mobile scenarios.

Eden Chen, General Manager of MC BU at Fibocom, said:

“AI-driven productivity is inevitably evolving as an essential to extend the capabilities of IoT devices, significantly improve the operational efficiency by enriching the IoT device with edge computing.”

“We are pleased to be at the forefront of the AIoT market to provide a comprehensive, highly integrated SC228 smart module solution for various industries, looking forward, we are optimistic to unleash the interconnected intelligence with our powerful smart module portfolio.”

Engineering sample will be available by late December 2023.

The post Fibocom Unveils 4G Premium Smart Module SC228 to Drive AIoT Applications in the Global Market appeared first on IoT Business News.

Fibocom proudly announced that its 4G smart module SC126-NA has received certification from a leading carrier in North America. SC126-NA is an LTE entry-level, high-performance IoT SoC module tailored for the AIoT market, receiving the certification has verified the capability of its operation in the local telecom operator’s network, further accelerating the deployment of AIoT applications in the regional market.

Fibocom, a global leading provider of IoT (Internet of Things) wireless solutions and wireless communication modules, is proud to announce a pivotal achievement for its 4G smart module SC126-NA receiving the certification from one of the leading carriers in North America.

Integrated with a quad-core processor and leveraged 11nm technology, SC126-NA is a high-performance smart module designed for the entry-level intelligent IoT market, now the module is fully capable of providing an integrated, seamless connectivity service to a wide range of AIoT terminals including smart wireless payment terminals, industrial handhelds, 4G PTT-over-cellular terminals by gaining the certification.

The global artificial intelligence IoT market is projected to reach high demand with the expansion of AI technology. As an essential in fostering the AIoT market growth, smart module empowers IoT devices with mobile computing capabilities, allowing real-time data processing and analysis, greatly reducing the decision-making timeline in critical scenarios for industry customers and improving overall efficiency. The validation of Fibocom’s SC126-NA smart module can shorten the certification cycle of customers’ terminal devices and ease the investment concerns for customers’ IoT projects.

Notably, Fibocom SC126-NA is equipped with an open Android operating system with rich multimedia processing capabilities. It can be connected to an FHD (1920 x 1080 @30fps) touchscreen, supporting multi-channel camera input, plus H.265 / H.264 encoding and decoding capabilities and integrating with facial recognition algorithm. Packaged in LCC + LGA form factor, the module offers maximum flexibility for customers to develop terminal devices for various market demands. In addition, SC126-NA is capable of providing precise positioning and navigation with GNSS. Furthermore, with the scalability to support a rich set of interfaces including MIPI / USB / UART / SPI / I2C, etc, Fibocom SC126-NA is an ideal smart wireless solution for various applications that require the integration of cellular communication and multimedia features. With the expanding landscape of AIoT applications in the global market, Fibocom developed a series of regional versions of SC126 to support the frequency bands in Europe and APAC, as well as Wi-Fi only version to satisfy the booming market demands.

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The fusion of Artificial Intelligence (AI) and the Internet of Things (IoT) is propelling us into a new era of interconnected intelligence. This synergy, often referred to as AIoT, holds the potential to revolutionize industries, enhance daily life, and enable unprecedented levels of automation and efficiency. In this article, we will delve into the world of AIoT, exploring its definition, key applications, benefits, challenges, and the promising future it holds for our interconnected world.

Defining AIoT

AIoT, or Artificial Intelligence of Things, is a convergence of AI and IoT technologies. It involves embedding AI algorithms and machine learning models into IoT devices, enabling them to process and analyze data locally and make intelligent decisions. AIoT leverages the power of data analytics and machine learning to extract valuable insights and respond to changing conditions in real time.

Key Applications of AIoT

1. Smart Home

In the realm of smart homes, AIoT is making homes more intelligent and efficient. Smart devices, such as thermostats, cameras, and voice assistants, use AI to learn user preferences and adapt to individual needs. These devices can optimize energy use, enhance security, and automate various household tasks.

2. Healthcare

AIoT plays a vital role in remote health monitoring and telemedicine. Devices equipped with AI can collect and analyze patient data, such as vital signs and symptoms, and provide real-time health recommendations or alerts. This technology improves the quality of healthcare and helps manage chronic conditions more effectively.

3. Industrial Automation

In manufacturing and industrial settings, AIoT is transforming operations. IoT sensors collect data from equipment and processes, while AI algorithms analyze this data to predict maintenance needs and optimize production. This reduces downtime, increases efficiency, and improves overall productivity.

4. Smart Cities

AIoT contributes to the development of smart cities by enhancing urban planning and management. Traffic lights, surveillance cameras, and environmental sensors use AI to analyze data and improve traffic flow, monitor security, and reduce pollution.

5. Agriculture

In smart agriculture, AIoT is revolutionizing farming practices. IoT sensors collect data on soil quality, weather conditions, and crop health. AI models analyze this data to make decisions about irrigation, fertilization, and pest control, optimizing crop yields and resource use.

6. Retail

Retail businesses use AIoT to enhance the shopping experience. Smart shelves can monitor inventory levels, and AI algorithms can analyze customer behavior and preferences to personalize marketing and promotions.

7. Autonomous Vehicles

The automotive industry is integrating AIoT in the development of autonomous vehicles. AI algorithms process data from sensors, cameras, and Lidar systems to make real-time decisions for safe and efficient self-driving.

8. Energy Management

AIoT is improving energy efficiency by allowing smart grids to optimize power distribution based on real-time demand and supply data. This reduces energy waste and supports sustainable energy practices.

Benefits of AIoT

The integration of AI and IoT offers numerous advantages:

1. Real-Time Decision Making

AIoT enables devices to make real-time decisions based on data analysis. This leads to faster responses to changing conditions and improved efficiency.

2. Enhanced Automation

By embedding AI in IoT devices, automation becomes smarter and more adaptable. Devices can learn from data and user behavior, making automation more effective.

3. Improved Predictive Analytics

AIoT systems can predict maintenance needs, security threats, and other critical events, reducing downtime and preventing issues before they occur.

4. Personalization

AIoT can provide a more personalized user experience by adapting to individual preferences and needs.

5. Energy Efficiency

AIoT optimizes resource use and energy consumption, making processes more environmentally friendly and cost-effective.

6. Cost Savings

By automating processes and reducing downtime, AIoT can lead to cost savings in various industries.

Challenges and Considerations

While AIoT offers numerous benefits, it also poses challenges and considerations:

1. Data Privacy and Security

Collecting and analyzing sensitive data using AIoT technology raise concerns about data privacy and security. Strong data protection measures are essential.

2. Complexity

Integrating AI into IoT devices and systems can be complex and require specialized expertise. Deploying and maintaining AIoT solutions can be a challenge for organizations.

3. Connectivity

Reliable internet connectivity is crucial for the seamless operation of AIoT devices. Expanding network coverage and ensuring robust connections are vital.

4. Energy Consumption

AIoT devices, especially those that rely on continuous data processing, can consume significant power. Energy-efficient designs are important to mitigate this.

5. Ethical Considerations

AIoT technologies may raise ethical concerns, particularly regarding data collection, sharing, and decision-making processes. Ethical guidelines and regulations are necessary.

The Future of AIoT

As technology continues to advance, the future of AIoT looks promising. Here are some trends and developments to watch for:

1. Edge AI

Edge computing combined with AIoT allows for data processing at or near the source, reducing latency and enabling real-time decision-making.

2. 5G Connectivity

The rollout of 5G networks will provide faster and more reliable connectivity for AIoT devices, enabling them to operate more efficiently and securely.

3. Quantum Computing

Quantum computing may revolutionize AIoT by providing unparalleled processing power, enabling more complex analyses and decision-making.

4. Ethical AI

Developments in ethical AI aim to address concerns about data privacy, fairness, and transparency in AIoT systems.

5. AIoT Ecosystems

AIoT ecosystems will become more interconnected, with devices and systems working together to provide a seamless and intelligent experience.

Conclusion

The synergy of AI and IoT, known as AIoT, is transforming industries and daily life by enabling real-time decision-making, enhanced automation, and predictive analytics. Challenges related to data security, complexity, and ethical considerations must be addressed to ensure that the benefits of AIoT are fully realized.

As AIoT technology continues to evolve, it will remain a driving force in our interconnected world, offering a glimpse into a future where devices and systems are smarter, more efficient, and adaptable, ultimately enhancing our quality of life and the efficiency of various industries.

The post The Synergy of AI and IoT: Unleashing the Power of AIoT appeared first on IoT Business News.

The year 2023 witnesses the ongoing redefinition of the technological landscape. Artificial intelligence and the Internet of Things join forces to reshape the fundamental structure of the business world. Together, they show the vast potential of intelligent connectivity, assisting businesses in streamlining operations, improving CX, and unlocking their full capabilities.

Collaborative harmony

The Internet of Things is rapidly changing modern businesses and entire sectors of the economy. This revolutionary technology allows for the gathering of huge data flows, resulting in an abundance of information. However, managing and interpreting it is an arduous activity.

Maximizing the power of the Internet of Things requires investment in advanced software solutions. Engineers can build machines that imitate complex behaviors and operate independently of humans.

AI and IoT examples are numerous. Let’s plunge into the most striking use cases.

Predictive maintenance

The Internet of Things implies using sensors that gather actual data from connected devices. Artificial intelligence then processes this information with exceptional accuracy.

The Internet of Things and AI can work together to shift maintenance approaches from reactive to proactive. This means potential issues can be identified before they become bigger problems, which can prevent costly breakdowns and reduce unplanned downtime. By anticipating maintenance needs, organizations can optimize operational efficiency and save money. This approach not only minimizes disruptions but also leads to significant cost savings.

As data flows are getting bigger, artificial intelligence becomes increasingly proficient at detecting subtle patterns that humans may overlook. This iterative process ensures continuous improvement, enhancing the accuracy and reliability of predictive maintenance models.

Proactive maintenance offers numerous advantages, such as heightened efficiency, prolonged equipment longevity, and increased customer contentment. Through harnessing up-to-the-minute observations furnished by the Internet of Things and intelligent algorithms, enterprises can guarantee the optimal functioning of their resources.

High-tech manufacturing

The entire sector is experiencing a considerable upswing in the implementation of artificial intelligence and the Internet of Things. According to Business Insider, the IoT market will reach an annual valuation of $2.4 trillion by 2027.

The interaction of the Internet of Things and intelligent software is ushering in an entirely new epoch. Significant manufacturing procedures can reap rewards from automated surveillance, resulting in enhanced production effectiveness, diminished mistakes, and anticipatory quality management.

The abundance of information collected from the Internet of Things acts as the cornerstone for artificial intelligence to conduct thorough examinations, revealing patterns and irregularities. Manufacturers acquire valuable perspectives on their procedures and make informed choices to amplify the effectiveness and minimize idle time.

Through ongoing monitoring and analysis of data, algorithms can detect initial indications of quality deviations, empowering business owners to implement measures that uphold product excellence and reduce the occurrence of defects.

The Internet of Things and intelligent algorithms help specialists implement automated monitoring of key processes and workflows. Real-time control by intelligent algorithms allows for the continuous observation of multiple parameters, including temperature, pressure, and performance metrics. Should any deviations or anomalies arise, automated alerts are generated, facilitating prompt intervention to preempt potential problems or equipment failures.

Enhanced management of logistics networks

Artificial intelligence and the Internet of Things produce significant outcomes for the logistics sector as well. In the face of regulatory modifications, escalating labor expenditures, amplified traffic, and unpredictable fuel prices, these technologies aid businesses in executing operations with ease and effectiveness.

The implementation of an intelligent framework empowers logistics professionals with enhanced monitoring of resources, remote administration of vehicle fleets, and heightened adherence to regulations. It facilitates the recognition and surveillance of essential assets, enables efficient logistics in smart cities, reduces concerns regarding quality, optimizes stock levels, and streamlines various procedures.

By implementing resilient systems for tracking resources, workflows can be automated and elements of artificial intelligence can be integrated, providing anticipatory maintenance, instantaneous notifications, and comprehensive oversight. Through the utilization of advanced sensors, businesses can monitor asset data without human involvement, obviating the necessity for conventional identification methods like QR codes or barcodes.

Through the transmission of real-time data from sensors, authorities can leverage advanced analytics to forecast the state of assets. By reducing periods of inactivity and optimizing the functioning of machinery, organizations can attain substantial enhancements in operational efficiency.

Real-time monitoring and management of fleets are facilitated by the Internet of Things. Effective and precise systems for tracking vehicles have demonstrated a capacity to diminish expenses associated with last-mile deliveries, with potential reductions in fuel consumption of up to 25% as indicated by Frost & Sullivan.

Installed sensors can identify warehouse capacity and send notifications to employees about specific requirements in detail.

Through the incorporation of GPS functionalities within smartphones and intelligent resources, the optimization of routes emerges as a fundamental aspect of transit logistics. Drivers can readily discern the most effective pathways, thereby diminishing fuel consumption and guaranteeing punctual delivery of products.

Personalized CX

The IoT and AI work together to collect vast amounts of data from different sources like smart devices, wearables, and connected appliances. It includes customer preferences, behavior, purchase history, and location details in real time. Businesses can gain valuable insights by integrating these devices into the customer journey, helping them understand individual preferences and requirements.

True magic happens when smart algorithms enter the picture. The amassed customer data is analyzed on a large scale to uncover patterns, correlations, and trends that might be overlooked by humans. By doing this, businesses obtain a comprehensive understanding of each customer’s preferences, habits, and aspirations. They can deliver highly personalized recommendations, offers, and experiences to their customers.

Algorithms enable dynamic pricing strategies, permitting businesses to offer tailored discounts and promotions. They also prove invaluable in generating custom content, such as personalized emails, newsletters, and targeted advertising campaigns.

Intelligent energy management

Artificial intelligence and the IoT revolutionize energy management and conservation in various sectors.

Within building management, devices like smart thermostats, lighting systems, and appliances collect data on energy consumption, which is subsequently analyzed by AI. This process identifies inefficiencies and provides suggestions for improvement.

The combination of AI and the Internet of Things has the capacity to optimize energy usage on a broader scale, encompassing cities or regions. Through the aggregation of data from intelligent meters and meteorological stations, algorithms scrutinize patterns of energy consumption, pinpointing opportunities for conservation. As a result, utilities and energy providers can forecast demand with enhanced accuracy, allocate resources in a more efficient manner, and reduce the necessity for costly investments in infrastructure.

Renewable energy sources also benefit from innovations. Smart algorithms optimize the performance of wind turbines, solar panels, and other renewable sources to achieve maximum power generation. Prompt identification and resolution of performance issues are possible through real-time monitoring.

By predicting fluctuations, artificial intelligence further contributes to renewable energy generation, aiding grid operators in effectively balancing supply and demand. This reduces dependence on fossil fuels and lessens the environmental impact.

Energy storage systems offer another application for innovative solutions. Intelligent algorithms optimize the charging and discharging of batteries, thereby extending their lifespan and minimizing overall storage costs.

Advanced agriculture

This sector is undergoing significant changes with the incorporation of artificial intelligence in the Internet of Things. Through the use of devices like soil moisture sensors and weather monitors, farmers are improving their irrigation, crop management, and pest control practices.

The integration of artificial intelligence, machine learning, robotics, unmanned aerial vehicles, and the Internet of Things in agricultural practices constitutes smart farming. This approach facilitates the monitoring of operations, decreases reliance on manual labor, and elevates the caliber and quantity of agricultural yields. It effectively streamlines and optimizes the cultivation of crops and livestock.

Precisely forecasting agricultural output is vital for efficient farm administration. Intelligent systems evaluate historical and contemporary data to furnish accurate prognostications over a duration.

Furthermore, innovative systems have the capability to assess the level of sunlight crops receive, enabling farmers to optimize their arrangements to enhance light penetration. Additionally, they utilize information from infrared sensors, satellite pictures, and thermal cameras to monitor the pace of plant growth and detect insufficiencies in nutrients.

Farmers assess relevant data on soil health, water levels, temperature, and pH. They employ drones to capture images of crops, detect problems, and forecast yield.

Connected healthcare

Modern medicine and patient care are no longer possible without artificial intelligence and the Internet of Things.

By utilizing wearable sensors and interconnected medical devices, physicians can remotely monitor vital indicators, medication compliance, and overall well-being. This facilitates the early identification of potential health complications and prompt intervention. Moreover, it diminishes the necessity for frequent face-to-face consultations, particularly for individuals with chronic ailments or residing in remote locations.

The application of artificial intelligence in predictive diagnostics is revolutionizing the process of disease detection and diagnosis. Through the analysis of extensive patient data, such as medical records, imaging examinations, and genetic details, AI algorithms can discern patterns and markers that have the potential to forecast the onset or advancement of diseases.

Connected healthcare also brings forth substantial advantages in the form of customized treatment strategies. Algorithms scrutinize unique patient information, encompassing medical records, genetic data, and treatment reactions, to devise personalized treatment plans. This tailored approach enables patients to receive more accurate and focused healthcare, resulting in enhanced treatment results and heightened patient contentment.

The growth of connected healthcare presents vast potential for transforming medicine. The projected increase in healthcare-related IoT revenues to over 135 billion by 2025 signifies the widespread recognition and acceptance of the value brought by pioneering technologies.

Smart retail

This is one of the key AI and IoT examples. Sensors and algorithms have brought about the idea of smart retail. By 2025, the retail sector empowered by the Internet of Things is projected to reach a valuation of $94 billion.

Retailers can deploy sensors throughout their stores to collect data on customer movements, interactions with products, and purchase patterns. These sensors capture information on foot traffic, duration of stay, and popular product areas, helping specialists gain a profound understanding of customer behavior.

By employing live monitoring of inventory levels, retailers can optimize their supply chain operations, guaranteeing the availability of popular products while minimizing surplus inventory.

Through the incorporation of artificial intelligence within the Internet of Things, entrepreneurs collect information pertaining to individual clientele, encompassing previous purchasing records, preferences, and browsing patterns. Consequently, they can personalize product suggestions, promotions, and discounts based on the specific requirements and interests of each customer.

Experts scrutinize up-to-the-minute data concerning demand, pricing strategies of competitors, and prevailing market conditions. They flexibly adapt pricing to optimize revenue and profit margins.

Intelligent technologies enhance store conditions and streamline operational efficiencies. As an illustration, sensors for temperature and humidity can oversee store environments, guaranteeing optimal conditions for perishable items or delicate merchandise. Artificial intelligence can analyze this information, prompting notifications or automating modifications to uphold ideal storage conditions.

Self-driving cars

Autonomous vehicles equipped with cutting-edge technologies are completely reshaping the way we commute and travel. At the heart of this revolution lies artificial intelligence of things.

They are equipped with an array of sensors that gather valuable data. So, such cars navigate and respond to dynamic traffic conditions with unparalleled precision. They spot potential hazards, react swiftly to unexpected events, and reduce the risk of accidents, ensuring safer transportation for both passengers and pedestrians.

Furthermore, this remarkable advancement harbors the capacity to enhance traffic control. Conventional systems frequently grapple with challenges such as congestion, suboptimal routing, and underutilization of road infrastructure. However, autonomous vehicles can accumulate extensive quantities of data pertaining to traffic patterns, road conditions, and vehicular motions. Through the dynamic adaptation of routes, the optimization of traffic flow, and the synchronization of signals, they can mitigate congestion, diminish travel durations, and amplify the overall efficiency of traffic.

As the prevalence of self-driving cars increases, traditional car ownership models are being challenged, giving rise to innovative mobility services. Consumers can seamlessly access shared autonomous fleets through mobile applications. This shift towards shared mobility not only alleviates traffic congestion but also provides cost-effective and environmentally friendly transportation options.

Smart cities

This concept once seemed a futuristic dream. But now it is becoming a reality. By introducing artificial intelligence in the Internet of Things, cities are transforming their infrastructures into smart systems that optimize resources, transportation, and public safety.

At the vanguard of innovation, the IoT and AI are propelling smart cities towards becoming vibrant and adaptive entities that prioritize the well-being of residents and enhance their everyday experiences.

A prominent illustration lies in the utilization of intelligent meters harnessing sensors to scrutinize and trace energy utilization. This empowers city authorities to optimize energy consumption. For instance, smart meters were effectively adopted in Barcelona, leading to a noteworthy 25% surge in water conservation and significant cost reductions.

Smart poles present a myriad of capabilities, encompassing illumination, wireless connectivity, and environmental surveillance. These astute structures amass and transmit data in real time, empowering city authorities to make well-informed choices founded on precise information. With the capacity to furnish high-speed internet connectivity and accommodate diverse functions, they possess the potential to transform urban landscapes on a global scale.

The paradigm of urban transportation is being reimagined thanks to the influence of artificial intelligence. As self-driving vehicles become commonplace, intelligent infrastructure will unlock their complete capabilities, be it in the form of autonomous cars facilitating food delivery or seamlessly catering to airport pick-up requirements.

Conclusion

The harmonious fusion of artificial intelligence within the Internet of Things has established the foundation for a revolutionary business transformation. With industries embracing these technologies, we are witnessing the emergence of pioneering solutions that streamline operations, bolster efficiency, and elevate decision-making procedures. To fully harness their potential, contemporary enterprises collaborate with top Internet of Things software development companies. Experienced IT providers deliver the expertise and customized software essential for navigating the intricacies of this rapidly evolving terrain.

The post The Synergy of IoT and AI: Revolutionizing the Future of Business appeared first on IoT Business News.

During MWC Shanghai 2023, Fibocom announces the launch of its 5G smart module SC151-GL empowered by the Qualcomm® QCM4490 Processor. The global version of SC151-GL aims to provide a “one unit fits for world” solution for 5G AIoT markets, and enables the access of mobile smart terminals to the 5G service anywhere, anytime.

Fibocom, a global leading provider of IoT (Internet of Things) wireless solutions and wireless communication modules, announces the availability of SC151-GL at MWC Shanghai 2023.

Based on the Qualcomm® QCM4490 Processor, Fibocom SC151-GL is the industry-first 5G smart module that supports mainstream frequency bands under 5G network architecture worldwide, which is crucial for customers that require global roaming on their devices to deploy the smart wireless solution faster, more efficient compared to the regional versions.

Fibocom SC151-GL provides a comprehensive smart wireless solution empowered by the Qualcomm® QCM4490 Processor. Compliant with 3GPP Release 16, the module is capable of offering Gigabit 5G experience, in addition to the support of Wi-Fi 6/6E, allowing the connections of multiple end devices simultaneously as well as the high-capacity of data throughput, these features can significantly improve the uplink performance, especially for the latency-sensitive scenarios like warehouse management and manufacturing detection. In terms of network utilization, the SC151-GL is also backward compatible with 4G/3G bands in addition to the compatability of 5G SA/NSA and EN-DC. It is worth highlighting that the module delivers a power-efficient solution for end devices enabled by the added-value TWT (Target Wake Time).

The convergence of AI and IoT is inevitable in the fast-growing digital transformation, and 5G is the key accelerator to implement the migration in 5G AIoT era. Fibocom SC151-GL is a “one unit fits for world” smart wireless solution for customers from the industrial handheld, industrial tablet, point-of-sale devices, body-worn cameras, PoC (push to talk over cellular) industries to minimize the R&D cycle and reduce hardware investments in the early stage of global deployment. Equipped with a set of rich interfaces including MIPI/ USB/ UART/ SPI/ I2C, etc., the module is scalable to meet the demands of various AIoT applications, and the support from software is fully capable of future upgrades to Android 18.

“The booming market of 5G has driven more and more IoT devices to evolve from 4G to 5G, especially for the smart devices such as industrial handheld terminals or tablets that require seamless roaming to satisfy the processing speed of edge computing,” said Eden Chen, General Manager of MC Product Management Center, Fibocom.

“We are confident to say that the launch of SC151-GL, the industry-first 5G smart module that integrates the capability to support global frequency bands in one unit will help our customers to lead the 5G transformation and digitalization more efficiently.”

The post Fibocom Launches the Industry-first SC151-GL, Accelerating the Global 5G AIoT Commercialization with One Highly Integrated Smart Module appeared first on IoT Business News.

IoT has revolutionised how we interact with technology and the world. It has created a network of interconnected devices that share data and insights, making our lives more efficient and convenient. As a result, IoT has become an integral part of our daily routines, ingrained in logistics networks, supply chains, smart cities, and much more.

While IoT has already significantly impacted our lives, integrating AI into IoT systems is the likely next step in its evolution, with its potential to help IoT systems become more efficient and effective. But is the autonomy and instant decision making, in what is essential a black box a cause for concern?

Let’s explore both sides of the coin, starting with the positive aspects of AI in IoT.

Benefits of AI

There are many ways in which AI has the potential to revolutionise IoT. Firstly, AI can process and analyse vast amounts of data generated by IoT devices more efficiently and effectively than traditional methods. Using machine learning algorithms, AI can identify patterns, derive insights, and make predictions based on the data collected from IoT-connected devices. This enables organisations to extract valuable information and act proactively.

Taking this a step further, AI could take over that decision-making process and implement new strategies or approaches based on changing data, conditions, and reactions without human intervention. This can increase efficiency, reduce human error, and improve productivity across various applications such as smart homes, industrial automation, transportation, and healthcare.

These better decisions will positively impact energy usage in IoT systems. Furthermore, by analysing data from sensors and devices, AI can identify energy consumption patterns and optimise efficiency. For example, in a smart building, AI can automatically analyse occupancy data to adjust heating, cooling, and lighting systems, resulting in energy savings. Meanwhile, by improving predictive maintenance of IoT-connected devices, AI can reduce downtime, optimise performance, improving overall equipment reliability.

A final promising opportunity for AI and IoT is in Edge Computing, which has been a topic of interest in IoT for some time now. Since AI can be deployed at the edge, it is possible that real-time decision-making could be enabled, and the need for constant data transmission to the cloud could be reduced. This would improve latency, bandwidth usage, and privacy while enhancing the overall efficiency of IoT deployments.

Challenges of AI

While AI brings numerous potential benefits to B2B IoT applications, some concerns and challenges must be addressed. First and foremost, data privacy and security, due to the amount of sensitive data being collected and processed by a technology which has full autonomy and yet is completely hidden from sight of humans.

Companies must ensure adequate measures to protect data from unauthorised access, breaches, and misuse. In addition, there is a clear need to improve the transparency of the decision-making processes of AI, including the ability to take back control and/or reverse decisions, so not to lose control over the system.

The reliability and accuracy of AI algorithms in B2B IoT applications are of utmost importance. Incorrect or unreliable AI predictions can have significant consequences, especially in critical healthcare, transportation, and manufacturing applications. Therefore, ensuring the accuracy and robustness of AI models, along with rigorous testing and validation, is essential to maintain trust and confidence in B2B IoT systems.

Of course, integrating AI with existing IoT systems can be complex and challenging. For example, B2B organisations may already have established IoT infrastructure, and integrating AI capabilities into these systems requires careful planning and implementation. In addition, compatibility, scalability, and interoperability issues may arise when integrating AI algorithms into various IoT devices and platforms.

There are also a couple of elephants in the room regarding AI implementation. Firstly, there is a concern about the shortage of AI experts and data scientists who can develop, deploy, and maintain AI systems effectively. As a new technology, organisations must invest in training programs and provide resources for upskilling employees to bridge this skill gap.

The second is regulation. There are numerous calls from governments, enterprises, and even the godfathers of AI to get regulation in place rapidly. As a result, any AI implemented into IoT applications today may well be subject to legal challenges tomorrow. Compliance will be essential, but right now, it will take a great deal of future-gazing to anticipate the likely regulations that come to pass.

Conclusion

Over-reliance on AI could lead to situations where humans lose control or understanding of underlying processes. This can result in unintended consequences, such as systems behaving unexpectedly or failing entirely.

As such, any AI implementation in IoT systems must be designed with human oversight and intervention to ensure that humans retain control over the technology. Additionally, it is essential to have fail-safe mechanisms in place to prevent such unintended consequences.

Overall, there are clear opportunities in integrating AI into IoT systems, I believe we must approach with caution, and take steps to bring AI into the world of IoT in a considered manner.

While in the past moving fast with new technologies has been a strong move to make, moving fast with a self-learning, autonomous technology carries greater risk, and is worthy of a little more caution.

The post The pros and cons of AI and IoT appeared first on IoT Business News.

Fibocom is presenting its cellular wireless modules and solutions at Computex 2023, the world’s leading tradeshow demonstrating the most up-to-date tech trends from May 30th to June 2nd. Fibocom launched the 5G RedCap module FG132-NA series in accelerating the massive deployments of 5G applications during the show.

Fibocom, a global leading provider of IoT (Internet of Things) wireless solutions and wireless communication modules, has demonstrated the leading-edge wireless IoT module solutions and embedded PC solutions at Computex from May 30th to June 2nd at Booth #I1010.

Featuring the commercialization of 5G applications, Fibocom has launched the 5G RedCap module FG132-NA series to enable the application scenarios such as industrial automation, FWA, smart wearables, and smart cities.

Introducing the 5G RedCap Module FG132-NA to Offer Affordable 5G Solution

During the show, Fibocom announced the global launch of its RedCap module FG132-NA series to expand the 5G deployments with a cost-effective, low power consumption, and ultra-reliable connectivity solution. Fibocom FG132-NA series modules are compliant with 3GPP Release 17 standard, supporting 5G SA and are backward compatible with LTE Cat 4 networks. In terms of hardware architecture, the module series is adopting 1T2R antenna design along with LCC+LGA and M.2 form factors to satisfy the customers’ expectations in a diverse of use scenarios.

The size of LCC+LGA form factor can be measured at 29*32mm, which is pin-compatible with Fibocom LTE Cat 4 modules for customers to upgrade to 5G smoothly. While the plug-and-play M.2 form factor offers a comprehensive solution for tablets and industrial gateways with a compact size of 30*42mm. By leveraging the 5G key advancements, FG132-NA supports up to 220Mbps downlink speed and 100Mbps uplink speed, as well as 5G slicing, 5G LAN, assuring the speed performance and network reliability in the daily operation of manufacturing factory, IPC, smart grids, etc.

High-reliability, Outstanding-performance Module Solution Accelerating the Deployments of 5G AIoT Applications

The number of connected IoT devices in the global market is expected to grow to 16.7 billion active endpoints according to the latest reports from IoT Analytics, and the number continues to grow at a fast speed in upcoming years. Fibocom is providing 5G/4G/LPWA/GNSS wireless modules and AI-enabled modules to an extensive of IoT applications, including:

• FWA devices such as IDU/ODU/Mobile Hotspot embedded with Fibocom 5G modules bring ultra-fast, low-latency broadband connectivity service for home/enterprise/manufacturing users.
• AI edge computing box embedded with Fibocom 5G module FM160/FG160 series will significantly improve the speed performance, which is of vital importance to help decision makers to access the real-time data and take actions instantly.
• Fibocom LTE Cat 1 module L610 offers a stable 4G network connection solution for mobile tracking scenarios, helping fleet managers to track the status of their assets in real-time.

Driving the Innovation of 5G-enabled PCs with Fibocom 5G Modules

With the rising trends of WFH (work from home), the demand for always-connected PCs stays at the top of people’s daily work life. Fibocom has demonstrated the best-in-class module solutions for connected PCs. Embedded with Fibocom FM350, the users of 5G PCs can enjoy a reliable connection anywhere, anytime. As a global leading provider of wireless communication modules and solutions, Fibocom has accumulated in-depth know-how in the PC market, looking forward, will put continuous efforts into propelling the connected PCs seamlessly.

On the opening day of Computex, Tiger Ying, CEO of Fibocom talked with the editor from local media partner Digitimes about the recent market trends and Fibocom’s global strategy.

Tiger Ying, CEO of Fibocom, said:

“Fibocom launched the first 5G module in 2019, in the past few years, we have achieved great performance in the global FWA market benefiting from the technical know-how we accumulated from the 4G era.”

“On the other hand, Fibocom has worked closely with mainstream chip providers to provide a one-stop total solution for FWA customers, which is of great help in reducing the time to market and smooth upgrade from 4G to 5G. Looking forward, Fibocom will keep providing the best-in-class wireless module products and solutions to our customers worldwide, enabling smart connectivity with perfect wireless experience.”

As the show continues, we welcome you to visit Fibocom stand at Computex 2023, booth #I1010 in hall 1.

The post Fibocom Showcases at Computex 2023, Unleashing the Value of 5G AIoT for Industry Transformation appeared first on IoT Business News.

Fibocom launches the 5G smart module SC151 with a comprehensive capability to empower the AIoT industry. Powered by the Qualcomm® QCM4490 Processor, the module offers elevated 5G cellular and Wi-Fi 6E connectivity for AIoT terminals, further boosting the commercialization of 5G AIoT applications.

Fibocom, a global leading provider of IoT (Internet of Things) wireless solutions and wireless communication modules, announces the global launch of 5G smart module SC151 to enhance AI-based applications with premium 5G and Wi-Fi 6E experience and high-performance processing capability.

Based on the Qualcomm® QCM4490 Processor, Fibocom SC151 can be used in a wide range of 5G AIoT scenarios in the global market, it is an ideal wireless solution for terminals such as industrial handhelds, point-of-sale devices, body-worn cameras, PoC (push to talk over cellular), etc.

Compliant with 3GPP Release 16 standard, Fibocom SC151 adopts a high-performance octa-core processor that allows applications to run smoothly, integrates a high-performance graphics engine to allow smooth video playing and multi-channel camera input. In addition to select AI capabilities, Fibocom SC151 extends its 5G connectivity by supporting DL 4×4 MIMO as well as UL 2×2 MIMO, roaming under both 5G SA and NSA network architectures, allowing backward compatability with 4G/3G bands.

SC151 also extends its advancements by supporting 2.4G+5G WLAN and Wi-Fi 6E, plus DBS (Dual Band Simultaneous) to increase the overall capacity and performance. Benefitting from the Qualcomm QCM4490 processor and its 3GPP release 16 capabilities that enable international carrier support, there are five variants of SC151 module series to support regional frequency bands in EMEA, Americas, APAC, etc.

The module also supports multi-constellation GNSS (GPS(L1+L5 Dual Frequency Bands)/GLONASS/BeiDou), which significantly improves position accuracy in mobile scenarios while greatly simplifying product design. SC151 is equipped with Android 13 operating system in preparation for subsequent OS upgrades in the future. With a rich set of interfaces including MIPI/ USB/ UART/ SPI/ I2C, etc., enabling flexibility and ease of integration to meet various application demands of the AIoT industry.

“The convergence of AI and 5G technology has impacted many aspects of the IoT industry, the use of AI compute for decision-making in IoT and data analytics will be crucial for efficient and effective industrial solutions,” said Eden Chen, General Manager of MC Product Line, Fibocom.

“Fibocom 5G smart module SC151 is the ideal wireless solution for customers to develop and extend next generation high performance applications with premium 5G and Wi-Fi 6E connectivity and AI capability. With the long lifespan of SC151, we are looking forward to achieving great success across the global AIoT market.”

“AI is an extremely important part of the IoT landscape, with the SC151 powered by the Qualcomm QCM4490 Processor, technology will become even more advanced for enterprises across the globe,” said Dev Singh, Vice President, Business Development and Head of Building, Enterprise, and Industrial Automation, Qualcomm Technologies, Inc. “Qualcomm Technologies is proud to collaborate with Fibocom to enable them to create such an innovative product for a diverse range of applications, especially as the AIoT landscape continues to evolve.”

The engineering sample of SC151 will be available starting Q2 2023.

The post Fibocom Launches 5G Smart Module SC151, Powering up 5G Connectivity for AIoT Industry appeared first on IoT Business News.

Delivers AIoT (Artificial Intelligence of Things) edge technology for autonomous driving, robotics, and mobility AI vision surveillance management.

Blaize® today announced a multi-year Memorandum of Understanding with Korea Telecom (KT) — Korea’s leading AI, big data, and cloud service provider.

The strategic collaboration brings AIoT (Artificial Intelligence of Things) edge device technical development cooperation for autonomous driving, robotics, and mobility AI vision surveillance management. Blaize and KT intend to coordinate, promote, and support the advancement of manufacturing and services requirements of AI development and education for on-device technology for AI market creation in Korea. The MOU will bolster their united relationship and foster a more robust channel for exchanging views on AIoT edge device manufacturing requirements.

KT plans to expand the development of on-device AI products at the terminal end that can minimize data usage and implement various functions to strengthen the AIoT (Artificial Intelligence of Things) service business that combines AI and IoT technology. For this, Blaize’s tightly coupled software and small form factor, low power, and high-speed data processing hardware deliver an end-to-end efficient, usable AI edge workflow that will help KT expand its AIoT efforts.

Through collaboration with development hardware partners like Blaize, KT plans to commercialize specialized terminals and services, such as intelligent IoT routing equipment, micro-mobility services incorporating AIoT technology, and AIoT autonomous driving logistics transport devices for use in distribution, logistics, and smart factories.

Dinakar Munagala, CEO and Co-founder of Blaize, said:

“Our expanded collaboration with KT in AIoT edge business advances our shared understanding of technical development in some of the key Blaize markets — automotive, mobility, and smart vision. We look forward to further extending Blaize hardware and software solutions, serving the 5G+, MEC, and cloud-based AIoT markets.”

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Quectel Wireless Solutions has announced its advanced 5G modules — which securely and reliably connect devices and people to networks and services — are available now with the NVIDIA® Jetson AGX Orin 32GB system-on-module (SOM).

With its Jetson edge AI platform, NVIDIA is accelerating the next wave of robotics, automation and artificial intelligence IoT. The platform’s power-efficient, compact and scalable capabilities include pre-trained AI models, software development kits and support for cloud-native technologies across the Jetson line-up.

As a global IoT solutions provider, Quectel’s products make life more convenient and efficient. Adding 5G modules to the Jetson ecosystem is set to make it easier for users to manage and build out deployments in smart cities, manufacturing, IoT, industrial applications and many other connected businesses and processes.

The latest NVIDIA Jetson offering, the Jetson AGX Orin 32GB SOM, has been integrated with the Quectel RM500Q series 5G sub-6GHz module. The most advanced module of its kind, it supports multiple concurrent AI application pipelines using an NVIDIA Ampere architecture GPU. With deep learning, vision accelerators, high-speed IO and fast memory bandwidth, the Orin enables complex AI models to solve problems such as natural language understanding, 3D perception and multi-sensor fusion.

The Orin SOM delivers up to 275 TOPS of AI performance with power configurable between 15W and 60W. This provides more than eight times the performance of the Jetson AGX Xavier in the same compact form factor, which makes the Orin ideal for robotics and other autonomous machine use cases.

“We’re delighted to announce that our RM500Q series 5G module supports the NVIDIA Jetson AGX Orin platform,” said Norbert Muhrer, President & CSO, Quectel Wireless Solutions.

“The combination of our ready-to-use Quectel 5G module and the Jetson AGX Orin platform helps simplify device development, improve product stability and accelerate time to market for customers’ terminals.”

Key features of the RM500Q series include LTE, in addition to 5G, as well as multi-constellation GNSS connectivity if desired. In addition, the module’s M.2 form factor and choice of USB 3.1 or PCIe 3.0 high-speed interfaces make it attractive to a wide range of device types and use cases. The module also offers optional voice over LTE (VoLTE) and Quectel’s Enhanced AT Commands.

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Quectel Wireless Solutions, a global IoT solutions provider, today announces that it has launched its new generation of multi-mode Smart LTE Cat 4 modules, the SC200E series.

The SC200E series delivers superior performance in LTE connectivity, multimedia functions and support for long lifespan IoT deployments, making it ideal for both industrial and consumer applications including smart POS, payment terminals, industrial handheld devices, automotive electronics and more.

“We continue to expand our best-in-class portfolio for IoT solutions, with our smart module product line ranging from entry level, to high-end and premium products to satisfy the requirements of various AIoT markets,” said Norbert Muhrer, President and CSO of Quectel.

“The launch of the SC200E series provides our customers with another great choice when developing advanced IoT applications for industries as varied as financial, retail, industrial, energy, health care, logistics and automotive to enable innovations and help build a smarter world.”

Based upon the Qualcomm QCM2290 platform which uses an 11 nm process, Quectel’s SC200E series adopts a 64-bit quadcore Arm Cortex-A53 processor at up to 2.0 GHz frequency, which enables the module to provide both greater power efficiency and reliable performance. Equipped with a powerful Adreno 702 GPU, the module also supports a dual Image Signal Processor (ISP). This ISP enables up to 25 MP or 13 MP +13 MP dual cameras to work at the same time and 1080p@30fps video codec capability. Given these advantages, the SC200E is an excellent option for IoT verticals that require advanced multimedia features such as smart POS terminals, industrial PDAs as well as systems in micro-mobility applications.

Quectel’s SC200E has the Android 12 operating system (OS) built-in and supports future iterative upgrades to Android 13 or 14, which enables IoT devices to stay up-to-date with the latest features and improvements in the OS. Additionally, the SC200E series fully meets Google’s GMS license requirements. The extended life cycle means the SC200E series can meet the high reliability and sustainable upgrades requirements of industrial IoT devices through to 2028.

In terms of communication capabilities, the SC200E supports multimode LTE cellular networks and short-range wireless communication technologies such as Wi-Fi and Bluetooth, so that terminal devices can flexibly access wireless networks according to different scenarios. In addition, the SC200E supports multi-constellation GNSS receivers (GPS/ BDS/ GLONASS/ Galileo/ QZSS/ SBAS) to achieve fast and accurate positioning.

The SC200E series is pin-to-pin compatible with Quectel’s previous-generation smart modules including the SC20/SC200R modules, so industry customers can efficiently upgrade their existing smart terminals and use SC200E to achieve better performance. The SC200E integrates a variety of interfaces such as LCM, camera, touch screen, microphone, USB, and UART, which greatly expands its application scenarios including in retail, industrial, home and other fields, and helps customers to accelerate the time-to-market of their devices.

In response to the different needs of various regions around the world, the Quectel SC200E series provides multiple variants, including SC200E-EM for EMEA/ Korea/ South Asia/ Latin America/ Australia/ New Zealand/ South Africa, SC200E-CE for China, SC200E-NA for North America, and SC200E-WF for global regions (Wi-Fi & Bluetooth only), all of which have achieved mass production, while the SC200E-JP variant for Japan is scheduled to be sampling in Q3 of 2022.

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