Electronic Enthusiast Network reports (by Li Wanwan) that Edge AI is the deployment of AI algorithms on edge devices, where computing occurs close to the user and data at the network edge, rather than centralized in cloud computing facilities or private data centers. Edge AI relies on edge computing power and algorithms; the computing power provides support, while the algorithms determine the scenarios where Edge AI can be applied and what functions it can achieve.
Mainstream Edge AI Algorithm Applications
Currently, the mainstream applications of Edge AI algorithms include face and key point detection. Key point monitoring quickly detects faces and marks facial coordinates, extracting key points of the face, including cheeks, eyebrows, lips, and nose, to achieve face alignment and accurately identify various attribute information, providing reliable support for face recognition.
Pedestrian attribute analysis obtains high-precision recognition of pedestrian attributes and actions through pedestrian detection, including gender, age, clothing category, clothing color, accessories, and behavior actions, providing rich structured information for efficient video material management and targeted marketing.
License plate and vehicle model detection and recognition detect the position of the vehicle, recognizing license plates and vehicle brand models, while supporting multi-stream inference, applicable in scenarios such as parks and traffic parking lots.
Object detection such as safety helmets can analyze pedestrian attributes to detect safety helmets and faces, determining whether safety helmets are worn through visual structural analysis, supporting training for recognizing various colors of safety helmets, and can also be used for detecting various objects.
Elevator electric vehicle identification and warning: the electric vehicle recognition algorithm detects and recognizes various types of electric vehicles. When an electric vehicle enters the elevator, the camera can issue an alarm and automatically upload alarm information,现场图像, and video data to the cloud platform, allowing management personnel to receive information, view现场情况, and take timely action.
Employee uniform recognition detects and recognizes various uniforms in offices or construction sites. Cameras can directly monitor whether personnel wear specified clothing, and if personnel are detected not wearing the specified uniform, automatic reporting of information,现场图像, and transmission to the cloud platform allows management personnel to receive information, view现场情况, and take timely action.
From an application industry perspective, in manufacturing, Edge AI algorithms are used for real-time monitoring of production line operational status, analyzing data collected by sensors in real-time to predict potential equipment failures and conduct preventive maintenance. This greatly enhances the stability and efficiency of the production line and reduces maintenance costs.
In smart city construction, Edge AI algorithms analyze traffic flow, vehicle operation status, and other data in real-time, providing decision support for traffic management departments. By deploying sensors and cameras at the roadside, traffic conditions can be monitored in real-time, automatically adjusting traffic signal timings to alleviate traffic congestion.
In the retail sector, Edge AI algorithms are used for customer flow analysis and product recommendations in smart stores. By installing cameras and sensors within stores, customer flow and shopping behavior data can be monitored in real-time, providing customers with a more personalized shopping experience.
In energy management, Edge AI algorithms monitor the operational status of power grids, oil pipelines, and other facilities in real-time, predicting energy demand and supply conditions to optimize energy utilization. By deploying sensors and edge computing devices on energy facilities, data can be collected and analyzed in real-time, providing decision support for energy management departments.
Real-World Applications of Edge AI in Security, Retail, Transportation, and More
After years of development, many companies are now involved in the Edge AI field, including chip manufacturers, algorithm developers, computing facilities, and comprehensive solution providers, and there are already numerous practical application cases.
For example, Hongsoft Technology has a wide range of layouts and practices in Edge AI applications. Hongsoft’s AI algorithms are widely used in smartphone cameras, enabling various smart photography functions such as face recognition, portrait segmentation, beauty mode, and night scene mode. These algorithms run on smartphone chips, achieving edge computing and ensuring real-time performance and efficiency in photography.
Hongsoft’s Edge AI technology is also applied in the smart security field. By deploying AI algorithms on cameras or other edge devices, functions such as face recognition, behavior analysis, and anomaly detection can be realized, providing intelligent solutions for security monitoring.
In the smart retail sector, Hongsoft’s Edge AI technology helps merchants achieve more accurate customer flow analysis, product recognition, and intelligent guidance. By deploying edge AI devices in stores, customer behavior data can be collected and analyzed in real-time, providing decision support for merchants.
Similarly, KunYun Technology has implemented its Edge AI solutions in many fields. For instance, in smart gas station solutions, KunYun has provided smart gas station solutions for nearly 1,000 gas stations in Shandong.
By integrating the Xingkong X6A edge mini-station AI computing hardware product with specific algorithms (such as smoking recognition, phone call recognition, personnel off-duty recognition, smoke and fire recognition, fire extinguisher recognition, and static electricity release time detection), intelligent detection and warning functions for high-risk areas such as refueling and unloading zones have been achieved.
This solution fully utilizes existing cameras and safety analysis solutions at gas stations, helping gas stations achieve pre-warning, in-process control, and post-evidence collection, enhancing the safety management efficiency of gas stations.
Smart chemical park solutions: in coal chemical parks, KunYun Technology provides AI intelligent video systems for intelligent analysis and hazard identification of key areas throughout the park.
This system uses AI technology to analyze non-compliant behaviors during hot work, high-altitude work, and confined space operations within the park, allowing for early warning and rapid response. Additionally, the system achieves comprehensive coverage, real-time monitoring, and effective control of chemical enterprises, important chemical installations, and hazardous chemical transportation vehicles, improving the safety management level of the park.
Smart traffic solutions: KunYun’s smart traffic solutions utilize AI technology for real-time processing and analysis of traffic data, achieving functions such as traffic congestion prediction, traffic signal control, and accident warning.
By deploying cameras and sensors at intersections and road sections, traffic flow, vehicle speed, and other information can be monitored in real-time, and intelligent algorithms can evaluate and predict traffic conditions, providing decision support for traffic management departments. This solution effectively enhances the intelligence level of traffic management and improves road traffic efficiency.
It can be seen that Edge AI is currently supporting the intelligent development of various industries. In addition to the aforementioned smart security, intelligent retail, smart manufacturing, and smart transportation, it also extends to smart agriculture, intelligent healthcare, smart logistics, and intelligent driving. With the continuous development of technology, the application scenarios of Edge AI will continue to expand.
Disclaimer: This article is original by Electronic Enthusiast Network, please indicate the above source when reprinting. For group discussions, please add WeChat elecfans999, for submission, exposure, and interview requests, please email [email protected].
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