AIoT: AI + IoT (Artificial Intelligence of Things)

Artificial Intelligence of Things (AIoT) is the fusion of AI (Artificial Intelligence) technology to the Internet of Things (IoT) infrastructure to achieve more efficient IoT operations.

IoT devices use the internet to communicate, collect, and exchange information. Every day, IoT devices generate 5 quintillion bytes (1 billion GB) of data, According to Cisco

AI can multiply the value of IoT by analyzing the data and utilized in problem-solving or decision making. Without AI, IoT would have limited value, IoT can promote the learning and intelligence of AI. AIoT can have various potential applications in the real world.

International Data Corporation (IDC) estimates that there will be 41.6 billion connected IoT devices, or “things,” generating 79.4 zettabytes (ZB) of data in 2025.

AIoT: AI + IoT (Artificial Intelligence of Things)

The IoT is empowered by three key emerging technologies

  • Artificial Intelligence (AI)
    Programmable functions and systems that enable devices to learn, reason, and process information like humans.
  • 5G Networks
    Fifth-generation mobile networks with high-speed, near-zero lag for real-time data processing.
  • Big Data
    Enormous volumes of data processed from numerous internet-connected sources.

Read: Samsung says 6G in 2028 with peak speeds of 1,000Gbps.

There are four major segments in which the AIoT is making an impact: wearables, smart home, smart city, and smart industry:

credit: visualcapitalist

Challenges while deploying AIoT

There are many challenges while deploying AIoT in the practice world. For instance, the edge computing issues in the AIoT devices. A huge amount of IoT data in networks are to be processed to achieving real-time responses, which requires high-performance AI for analyzing the huge data, it causes the latency in the problem solving or in decision taking of the device.

The security and privacy issue is another main considerable challenge in AIoT applications.

AIoT Practical Examples

Drone Traffic Monitoring

Drones are the perfect eye-in-the-sky for traffic monitoring, In smart cities, there are several practical uses for AIoT. If we can able to monitored the traffic in real-time then we can able to adjust the traffic flow.

when we deploy AIoT based drone it can monitor a large area, they can transmit traffic data, and then AI can analyze the data and make decisions about how to best alleviate traffic congestion with adjustments to speed limits and timing of traffic lights without human involvement.

Smart office buildings

a smart building can control building access through facial recognition technology. he combination of office cameras and AI that can compare images taken in real-time and check-in database to determine who should be granted access to a building.

In a similar way, employees wouldn’t need to clock in, or attendance for mandatory meetings wouldn’t have to be completed, since the AIoT system takes care of it.

Autonomous Delivery Robots

Amazon Scout autonomous delivery robot already begin making deliveries to customers in the Irvine, Calif areas. Robots have sensors that gather information about the environment the robot is traversing and then make moment-to-moment decisions, route planning, navigation.

Artificial Intelligence of Things Potential Areas

  • AIoT for smart city and city brain
  • Large-scale sensor networks for AIoT
  • Cloud, edge, fog, and dew computing for AIoT
  • Machine learning and deep learning for AIoT
  • 5G technology enabled AIoT
  • Unmanned Aerial Vehicle (UAV) aided AIoT
  • Mobile computing and Location-Based Services (LBS) for AIoT
  • Security and privacy in AIoT
  • Artificial Intelligence (AI) algorithms for AIoT
  • Internet of Things (IoT) technologies for AIoT
  • AIoT-based innovative applications and services

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