The convergence of AI (artificial intelligence) and IoT (Internet of Things) has unleashed huge potential for global enterprises.
When the IoT sensor detects external information, it replaces it with a signal that can be distinguished by humans and machines, and its AI can help build intelligent machines, learn from these data, and support the decision-making process with little human interference.
The use of the Internet of Things is exploding, and by the end of this year, it is expected that there will be as many as 50 billion connected devices. Combined with AI, this new technology wave can bring new opportunities and change the way the entire industry operates.
Autonomous driving always inspires people’s imagination, but it is a good example of how artificial intelligence and the Internet of Things work together. Autonomous vehicles (AVs) are equipped with sensors and need to continuously collect massive amounts of data about their surroundings. These data are processed into intelligent insights using artificial intelligence models, enabling the vehicle’s navigation system to negotiate the environment in real time and perform complex path planning.
Datatang is oriented to the field of intelligent driving research, providing 3D image annotation, scene semantic segmentation, pedestrian recognition, lane line recognition, obstacle recognition and other AI data products, as well as intelligent driving data collection and intelligent driving data annotation customized services.
Quality inspection based on computer vision is one of the largest application areas of artificial intelligence. Automatic optical inspection scans the quality defects of industrial machinery. Once they are identified, the semi-supervised ML algorithm model classifies the image as a fault category or predicts planned maintenance.
AI-based IoT solutions provide companies with predictive maintenance applications to predict equipment failures in advance.
According to Gartner’s survey, there will be 20 billion IoT devices connected together by 2020. According to Statista’s prediction, by 2030, about 50 billion IoT devices will be installed worldwide, and all devices from wearable devices to train operations will use this device. This universality will make them attractive targets for attack.
As a countermeasure, AI-enabled network security systems can detect network vulnerabilities, protect valuable data and prevent network attacks where AI systems can understand normal activity patterns, and determine when abnormal activities occur, thereby reducing the frequency of false alarms and possible Shows that a network attack has occurred.
With the outbreak of COVID-19, the integration of the Internet of Things and AI (AIIoT) has received widespread attention to meet the needs of intelligent health monitoring and pandemic management.
Wearable IoT sensors can track patient vital signs and update them in real time to doctors and nursing staff to remind them of any major health events. AI combined with machine learning algorithms can analyze large amounts of data to gain insight into the overall health of people. This eliminates the need for any manual intervention to maintain records and frees up medical staff to deal with important tasks such as personal care. With the outbreak of COVID-19, the integration of the Internet of Things and AI has received widespread attention to meet the needs of intelligent health monitoring and pandemic management.
The Internet of Things and artificial intelligence can play a role in reducing energy consumption. In any industry, HVAC systems account for a large part of the total energy consumption of a building, and account for a large part of the total energy consumption. The general system accounts for 40% of the building’s energy consumption. Machine learning programs learned from past efficiencies have been proven to reduce energy consumption by 20%.
Smart street lights equipped with IoT sensors can collect data about pedestrians and pedestrians, enabling the system to save up to 80% of energy expenditure. AI functions and machine learning and deep learning algorithms will parse the data generated from IoT sensors to track real-time energy consumption.
Datatang’s own data set “19928 street scene human segmentation & vehicle detection data”, the data diversity includes multiple scenarios (multi-vehicle scenarios, fewer-vehicle scenarios, speed limit scenarios), multiple weather distributions, and different time periods. In terms of labeling, the visible parts of the human body are segmented and labelled, and vehicles and traffic signs are labelled in rectangles. The data can be used for tasks such as human detection, human semantic segmentation, and vehicle detection in street scenes.
In short, from the Fortune 500 to start-ups, the demand for increasingly intelligent IoT in various industries will continue to grow. Using artificial intelligence to enhance the Internet of Things has the potential to open up opportunities to create new products. Machine learning, natural language processing (NLP) and other disruptive technologies encourage the acceleration of interactions between enterprises.
The combination of the Internet of Things and artificial intelligence is the inevitable result of the development of the two. The Internet of Things needs to play a greater role through artificial intelligence in order to continuously expand the application boundaries of the Internet of Things. This is also one of the core demands of the development of the Industrial Internet. And artificial intelligence also needs the important platform of the Internet of Things to complete its landing applications.