The Internet of Things refers to the connection of various devices and objects through the Internet so that they can communicate with each other and exchange data. With the continuous advancement of atechnology and the continuous expansion of applications, the Internet of Things has played an important role in realizing device interconnection, data sharing and intelligent applications. However, with the continuous expansion of the scale and complexity of the Internet of Things, traditional data processing and decision-making systems are often unable to meet the needs, which has given birth to the new concept of AIoT.

What is AIoT

AIoT, or artificial intelligence for the Internet of Things, is a new type of technology that combines artificial intelligence technology with the infrastructure of the Internet of Things. The purpose of AIoT is to improve the efficiency of the Internet of Things, improve human-computer interaction, and enhance data management and analysis capabilities.

How does AIoT work?

Artificial intelligence is a technology in which computer systems simulate the process of human intelligence, and is usually applied in fields such as natural language processing, speech recognition, and machine vision.

IoT is a system of interconnected computing devices, mechanical and digital machines or objects. These devices have unique identifiers and are capable of transmitting data over a network without human-to-human or human-to-computer interaction. Think of a heart monitor implant for a person, a car with built-in sensors to alert the driver when tire pressure is low, or anything else that can be assigned an Internet Protocol address and transmit data over a network.

AIoT combines these two technologies in a transformative and mutually beneficial way. AI adds value to IoT through machine learning and improved decision-making processes; IoT adds value to AI through connectivity, signaling and data exchange. AIoT can improve business and its services by creating more value from the data generated by IoT devices. AI enables IoT devices to use collected big data to better analyze, learn and make decisions without human intervention.

In AIoT devices, AI is embedded in infrastructure components such as programs and chipsets, which are all connected using IoT networks. APIs are then used to ensure that all hardware, software, and platform components can function and communicate together without end user effort.

At runtime, IoT devices create and collect data, which is then analyzed by artificial intelligence to provide insights and improve efficiency and productivity. AI uses processes such as data learning to gain insights. AIoT data can also be processed at the edge, meaning that data from IoT devices is processed as close to those devices as possible to minimize the bandwidth required to move the data while avoiding possible delays in data analysis.


How wireless transmission technology is applied to AIoT

Wireless transmission technology plays a vital role in AIoT.

Wi-Fi: Wi-Fi technology is widely used in scenarios such as smart homes and smart cities. In smart homes, Wi-Fi can be used to connect smart appliances, such as smart TVs, smart speakers, smart lamps, and more. In smart cities, Wi-Fi can be used to collect sensor data and transmit it to the cloud for analysis to achieve intelligent city management.

Bluetooth: Bluetooth technology is widely used in scenarios such as smart home, smart office, and smart health. In smart homes, Bluetooth can be used to connect devices such as smart door locks, smart curtains, and smart home centers. In a smart office, Bluetooth can be used to connect devices such as smart printers and smart speakers. In the field of smart health, Bluetooth technology can be used to connect wearable devices, blood glucose meters, heart rate monitors and other devices, and transmit data to mobile phones or the cloud for analysis.

Zigbee: Zigbee is a low-power, short-range wireless communication technology commonly used in sensor networks in smart homes. Zigbee devices can be connected to the Internet through a gateway to transmit sensor data to the cloud for analysis, such as temperature, humidity, light intensity and other data. This data can be used for intelligent temperature control, lighting, security and other systems to improve home comfort and energy efficiency.

LoRaWAN: LoRaWAN is a low-power, long-range wireless communication technology commonly used for IoT devices in smart cities. LoRaWAN devices can connect to the cloud through a gateway and transmit sensor data, such as the filling level of garbage cans, the usage of parking spaces, and so on. These data can be used for intelligent city management, such as automatic cleaning of trash cans, intelligent navigation of parking spaces, etc.

Wireless transmission technology is an integral part of AIoT, it can provide efficient and reliable data transmission for AIoT, and provide strong support for intelligent application scenarios

Applications and Examples of AIoT

AIoT (Artificial Intelligence in the Internet of Things) has a wide range of applications, some of the main examples include:

Smart Cities: Using sensors, lights and other smart technologies to collect data to help improve the efficiency of city operations, drive economic growth and improve the quality of life for residents.

Smart retail: Retailers use smart cameras to recognize shoppers' faces, detect if they have scanned an item and pay for it.

Smart home: smart appliances learn through human-computer interaction and response, and AIoT devices can store and learn user data, understand user habits, and provide personalized support.

Business and Industry: Manufacturers use smart chips to detect whether equipment is functioning properly, when parts need to be replaced, etc.

Social media and HR: AIoT tools can be integrated with social media and HR-related platforms to create AI decision-making as a service function for HR professionals.

Self-driving cars: Self-driving cars rely on multiple cameras and sensor systems to collect data, monitor driving conditions and look for pedestrians.

Autonomous delivery robots: Sensors collect data about the robot's environment, such as a warehouse, using AI to make path-planning-based decisions.

Healthcare: Medical devices and wearables collect and monitor real-time health data, such as heart rate, and can identify anomalies such as irregular heartbeats.

AIoT's opportunities and challenges for the future

AIoT will have an impact on wearable devices, smart homes, smart cities and smart industries.
Wearable devices such as smart watches are not only capable of monitoring and tracking user preferences and habits, but also have great application potential in health technology and sports and fitness. The global wearables market is expected to exceed USD 87 billion in revenue by 2023.

Smart homes can increase energy efficiency by using appliances, lighting, electronic devices, etc. to understand homeowners' habits and develop automated "support" Dollar.

Smart city innovations invest in improving public safety, transportation, and energy efficiency, and the use of artificial intelligence in traffic control has become crystal clear.

In the future, AIoT innovation will accelerate, including edge computing, smart thermostats, smart home appliances, home robots, self-driving cars, voice AI, smart speakers, natural language processing, electronic payment voice authentication, visual artificial intelligence, massive object detection, edge Fields such as video analysis and super 8K resolution. Companies that ignore IoT risk being left behind, so AIoT will become an increasingly mainstream technology in the coming years.