The Blend of AI and IoT Wireless Connectivity

By Saumitra Jagdale

Freelance Technology Writer

March 29, 2022


The Blend of AI and IoT Wireless Connectivity

Emerging IoT technology contributes to the growth of OEMs in various sectors as it helps collect massive amounts of data from multiple sources. Although it is complex to collect, process, and analyze this load of data, the blend of AI with the help of IoT has the power to revamp the operation of industries, businesses and economies.

IoT is basically about sensors attached to everyday machines that offer data streams through the internet. IoT follows five steps:

  1. Create: The network of sensors that collect the data
  2. Communicate: Transfer the collected data to a central location for processing
  3. Aggregate: Integrating the data
  4. Analyze/Augmented Intelligence: Extracting helpful information for the data
  5. Act/Augmented Behavior: Performing actions based on the extracted information

While IoT concerns acquiring data from a device's surroundings, artificial intelligence focuses on learning from that data and experience. The data obtained from the sensor can be analyzed with AI, helping businesses make informed decisions within optimal budgets.

Partnering AI with IoT helps achieve agile solutions by managing and analyzing relevant information from raw data. The analysis ensures accuracy and provides balanced personalization with confidentiality and data privacy, maintaining security against cyber attacks.

Cyber Security and Communication Protocols 

With regard to security measures, network protocols form the foundation for safe end-to-end communication between devices. The systems constituting heavy computational data are even more prone to cyber-attacks. Hence, the compatibility of protocols with hardware evaluates the system's overall security.

Some of the protocols compatible with the emerging combination of AI and IoT are:

  • Matter: an application-layer connectivity standard designed to create a reliable and secure wireless protocol to connect all IoT devices and networks in homes. The Matter protocol uses the existing IP technologies such as Wi-Fi and Thread to build a unified wireless connectivity ecosystem for smart homes. IP-based networking provides manufacturers with simplified development while improving device compatibility for consumers.  
  • OpenThread: an IPv6-based networking protocol designed for low-power IoT devices in a wireless mesh network called Wireless Personal Area Network (WPAN). It is a portable and flexible open-source implementation of the Thread networking protocol that is used to accelerate the development of products for connected homes and commercial buildings.
  • Zigbee: a standard-based wireless technology developed to enable low-cost, low-power networks. In contrast to Wi-Fi networks that are used to connect end nodes to high-speed networks, Zigbee features much lower data rates by using a mesh networking protocol to avoid hub devices and creates a self-healing architecture.

EFR32MG24 Series 2 Multiprotocol Wireless SoC

Credits: Silicon Labs

When it comes to applications such as smart homes, lighting, and building automation products, Silicon Labs’ EFR32MG24 Wireless SoCs are suitable for mesh IoT wireless connectivity with the help of protocols like Matter, Openthread, and Zigbee.

Credits: Silicon Labs

EFR32MG24 offers high-performance 2.4 GHz RF, low current consumption, and an AI/ML hardware accelerator. It also has a secure vault that enables IoT device makers to create intelligent and energy-efficient products that are protected from remote and local cyber-attacks.

The Blend of AI and IoT

Most hardware applications demand AI functionalities for modernizing the objectives of the use cases; thus, the amalgamation of AI and IoT creates an ideal ecosystem for data collection via sensors. AI in the IoT provide a wide variety of advantages for businesses and consumers, including ease in operations, increased scalability, and improved client services and satisfaction.

Saumitra Jagdale is a Backend Developer, Freelance Technical Author, Global AI Ambassador (SwissCognitive), Open-source Contributor in Python projects, Leader of Tensorflow Community India, and Passionate AI/ML Enthusiast.

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