The popularity of ChatGPT has set off a new wave of artificial intelligence development, accelerating the spread of AI to more application fields such as industry, retail, smart homes, smart cities, etc. On the application side, a large amount of data needs to be stored and calculated, and relying solely on the cloud can no longer meet actual needs. , edge computing perfects the last mile of AI applications.
Edge computing is currently in the early stages of its explosion, and the business boundaries in the industry chain are relatively blurred. A single manufacturer, not only needs to consider integration with business scenarios but also needs to have the ability to adapt to changes in business scenarios from a technical level. It also needs to ensure high compatibility with hardware equipment and engineering capabilities for project implementation.
Edge computing industry applications are accelerating their implementation
In the field of smart cities
Comprehensive inspections of urban properties currently generally adopt the manual inspection model. The manual inspection model has the problems of being time-consuming, laborious, and costly, relying on individuals in the process, poor coverage and inspection frequency, and lax quality control. By applying AI technology to mobile inspection scenarios, the company has built an urban management AI smart inspection vehicle. The vehicle uses technologies such as the Internet of Things, cloud computing, and AI algorithms, and is equipped with professional tools such as high-definition cameras, vehicle-mounted displays, and AI edge servers. Equipment, combined with the inspection mechanism of "smart system + smart machine + employee assistance", promotes the transformation of urban governance from personnel-intensive to mechanical intelligence.
In the field of smart construction sites
The smart construction site solution based on edge computing deeply integrates AI technology and applies it to the safety monitoring work of the traditional construction industry. By placing an edge AI analysis terminal on the construction site, it completes the independent research and development of visual AI algorithms based on intelligent video analysis technology and detects undetected objects at all times. Events (such as detecting whether to wear a helmet), provide personnel, environment, security, and other safety risk point identification and alarm reminder services, proactively identify unsafe factors, AI intelligent duty, save labor costs, and meet the needs of personnel and property safety management on the construction site.
In the field of intelligent transportation
The Cloud-edge architecture has become the basic paradigm for application deployment in the intelligent transportation industry. The cloud side is responsible for centralized management and some data processing, the edge side mainly provides edge data analysis, calculation, and decision-making processing, and the terminal side is mainly responsible for business data collection.
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