Artificial intelligence, 5G, Internet of Things, which technologies are changing human society?

liu, tempo Date: 2021-07-19 14:47:45
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When artificial intelligence or AI meets the Internet of Things, AIOT was born! —Namely: artificial intelligence of the Internet of Things. So, what is AIoT? What is its purpose?



Internet of Things



The Internet of Things is the ever-increasing number of devices and sensors that are connected to the Internet and capable of relaying data. The Internet of Things is helping every industry from transportation to retail to healthcare to seek to collect and utilize as much data as possible for operational optimization.



When we witness the explosive growth of the Internet of Things (IoT), most people may think: “Great, we will get a lot of data!” But with the accumulation of massive data sets across industries, people’s topics may shift to: “Great, how do we understand so much data?”



The Internet of Things is an emerging technology that can connect virtual and real objects, whether it is a mobile phone, tablet or wearable device, virtual assistant, smart home appliance, etc. Globally, billions of devices can communicate with each other and share information, and can collect real-time data from these devices simultaneously and continuously.



According to IDC data, by 2025, there will be 41.6 billion IoT connected devices worldwide, generating 79.4 ZB of data per year. By 2024, the Internet of Things market is expected to reach US$2.7 trillion, and this explosive growth will continue.

Internet of Things


Artificial intelligence



Artificial intelligence is emerging as a powerful analysis tool that can obtain information and find patterns in huge data sets faster and more accurately than data scientist teams. When applying AI to IoT device data, you will get intelligent analysis.
The original AI was that IBM’s Deep Blue defeated the chess master Gary Kasparov (Gary Kasparov) and Watson defeated everyone (Jeopardy!). Especially with the introduction of virtual assistants such as Siri and Alexa and the addition of facial recognition software, artificial intelligence (AIoT) combines AI and IoT infrastructure to improve IoT.



AI’s powerful data analysis capabilities can help extract meaningful information and insights from the data collected by IoT devices. Artificial intelligence can also help IoT devices interact with humans and other objects and make autonomous decisions. IoT devices are like the terminals of the nervous system, and AI is the brain that controls the nervous system, processes the information from the terminals and makes decisions.



Internet of Things + AI



The Internet of Things artificial intelligence is leading a smarter future. For example, smart homes can now send data to alert homeowners of water leaks when they are not at home, and turn off faucets to minimize damage.



Smart cities can alleviate traffic problems by analyzing traffic flow patterns and adjusting the settings of traffic lights, so as to adapt to unexpected traffic accidents or event events that generate more than normal traffic.



Smart wearable devices can report patient health data to doctors, help them track chronic diseases and remind them of health crises, so as to respond quickly in the event of a medical emergency.



AI helps identify anomalous patterns in massive data sets and sends alerts when the situation deviates from the observed norms. Therefore, it can identify abnormal patterns earlier, faster and more accurately. Companies can use AI to identify and mitigate potential risks, help companies avoid costly unplanned downtime, increase operational efficiency, and improve products and services.



Application of AIoT



The four main types of AIoT applications are:
Wearable devices: such as smart watches, augmented/virtual reality (AR/VR) and wireless earplugs.
Smart home applications: such as smart home appliances and home security;
Smart grid, street lights, public transportation and other aspects of smart cities;
Smart industry applications, such as autonomous manufacturing robots, automated supply chain management and predictive maintenance.
IoT devices contain sensors that can collect many different types of data, such as temperature, pressure, humidity, air quality, vibration, and sound. The almost infinite combination of different market segments and many measurement parameters in AIoT will make many applications possible.



Smart home and smart building



IoT sensors installed around the building can monitor the activities of people and adjust temperature and lighting to maximize energy efficiency. AIoT can also control access to buildings through facial recognition technology.



The combination of connected cameras and AI can analyze faces against the database in real time to determine who should be granted access to the building. Record any unidentified persons or unusual activities, and send alerts to the central hub for decision-making.



Smart industry



AIoT will accelerate the implementation of task-based robots in manufacturing, and extensive use of digital technology in product design, development and production. In addition, AIoT can also help companies monitor their trucks, ships, or tanker fleets, and identify unsafe driver behavior or vehicles that require maintenance. During transportation, AIoT can help maintain the cold chain of critical supplies, such as medical drugs that are very temperature-sensitive.



Smart retail
AIoT can provide value to the retail industry in many ways. By using AIoT, stores can more closely monitor supply and demand without manual intervention, and replenish inventory accordingly, thereby saving costs. By using a camera system that tracks shoppers with AI analysis, stores can collect information about customer gender and product preferences to tailor product recommendations. Smart cameras can help simplify the checkout process and minimize waiting time. Autonomous robots controlled by AIoT can be used to deliver goods.



Smart City



In smart cities, AIoT can help monitor the flow of drones that fly over the city and transmit flow data. The artificial intelligence can then analyze the collected data and reduce congestion by adjusting the speed limit and time of traffic lights. The system can also detect and respond to accidents quickly and effectively.



In addition, cities with flood problems can install sensors in storm drains and collect data for analysis to drain storm drains and prevent floods. Smart grids can actively manage energy imbalances in the grid to prevent the spread of power outages. Of course, the most concerned AIoT application in smart cities is self-driving cars. Many sensors can be installed on electric vehicles for fleet management to optimize utilization, minimize accidents and improve fuel efficiency.



As a rigid demand of the industry, security is the most important scenario for AI landing, and it has become a battleground for artificial intelligence.



AI technology has penetrated into all aspects of the industry. Taking the security field as an example, the trend of combining video surveillance with AI, big data, cloud computing, edge computing and other technologies is getting closer and closer. TSINGSEE Green Rhinoceros Video focuses on the new AI + video ecology and realizes full-scene empowerment. EasyCVR visual video surveillance based on AI intelligent analysis, integrated AI + video intelligent analysis, big data and other technologies, based on video surveillance systems, can help cities, traffic, Multiple scenarios such as security, medical care, education, etc. realize visual perception.



EasyCVR transforms video into more valuable information. Combining with big data and cloud computing technology can form a huge resource information database, providing powerful information support and auxiliary decision support for the industry.



Smart medical



AI can help humans actively manage chronic diseases and minimize expensive hospitalization. For example, collecting patient data for analysis through wearable devices enables doctors to remotely monitor the patient’s vital signs and blood glucose levels in real time. Artificial intelligence-assisted diagnosis will also reduce the workload of doctors and shorten the time required to obtain medical advice. Finally, AR/VR and cross-reality technologies can be used to train medical students on virtual patients and help patients recover.



Climate change



Climate change may be the biggest challenge facing mankind. In response, AIoT can be used to make agriculture and renewable energy smarter. Farmers can use drones to investigate their crops and determine whether it is drought or flooding. AIoT technology can help adjust the water system accordingly. AIoT can also be used to monitor the weather and determine outbreaks of plant diseases. On the other hand, AIoT can be used to manage renewable energy facilities. For example, by monitoring the wind speed, temperature, and humidity of wind turbines or solar farms, companies can reduce the risk of catastrophic damage or personal injury.



Successful implementation of AIoT standards



In addition to the big data collected by IoT devices and AI, 5G is critical to the success of AIoT. A functional 5G network is needed to transmit large amounts of data collected from IoT devices. For example, during remote surgery, it is necessary to stream video in real time to ensure patient safety and surgical success. In any case, data standardization is also essential. The AI algorithm is only as good as the data obtained. Lack of data standards will lead to landfills.



In addition, there is an aspect of AI ethics. Reports have pointed out that there are gender discrimination and racial discrimination in the algorithm. For example, image recognition software has poor accuracy when recognizing non-Caucasian faces. This prejudice can even be life-threatening when the software cannot accurately diagnose patients in a specific population.



Data scientists must be more careful to avoid prejudice; in addition, massive data sets that are equally attractive to data scientists and hackers must also be protected. The international standardization of network security will be a constructive step.



In addition, the cost of hardware (mainly high-performance CPU chips) will become a major bottleneck in the development of AIoT. Finally, the balance between energy consumption and analytical performance at the IoT device level must be resolved. Edge computing is a potential solution, and smart things will become smarter. One day, artificial intelligence will be used to help people manage all these Internet of Things.

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