Currently, artificial intelligence (AI) is opening a new turning point in many industries around the world, including the electricity industry. The rapid development of AI has brought about significant improvements in process automation, increasing accuracy and efficiency in the management, operation and maintenance of electricity systems.
The author group of PC Quang Tri received the Second Prize at the Closing and Awarding Ceremony of the 17th National Technical Innovation Contest - Photo: TUAN VIET
Previously, checking the power grid required a lot of effort and time and often did not achieve the desired accuracy due to dependence on human factors. In order to promote the achievements in using unmanned aerial vehicles in management fields, focusing on researching UAV flying drones and applying IoT in programming and setting up flight routes, controlling flights automatically to collect data (images, videos) through AI systems, the author group of Quang Tri Power Company (PC Quang Tri) has built the topic "Research and application of IoT technology integrated with GIS database to set up automatic flight mode for UAV devices, collect and process distribution grid image data, automatically warn of grid safety risks using artificial intelligence".
The project chaired by Director of PC Quang Tri Phan Van Vinh, which just won the Second Prize at the 17th National Technical Innovation Contest (2022-2023) organized by the Vietnam Union of Science and Technology Associations and the Vietnam Fund for Supporting Technical Innovation (VIFOTEC), is a typical example of applying IoT in solving specific challenges in the electricity industry.
This topic approaches the problem in a comprehensive, creative and focused way, applying IoT and AI to the field of power grid management and maintenance, focusing on the application of IoT in the flaycam automatic flight control system, combining AI to identify abnormal objects on the power grid.
The novelty of this topic comes from the combination of two main fields: AI and autonomous flight programming drones. In the increasingly developing environment of information technology, AI has played an important role in data processing and image/video analysis. Drones are increasingly used in monitoring and managing power grid infrastructure, but data processing from drones still requires human intervention.
Combining drones with AI improves automation and reduces human dependence. Using drones/UAVs with autonomous flight programming for image/video collection reduces time and costs compared to traditional methods. Combined with AI, safety risk detection can be done quickly and efficiently, enhancing the ability to respond and handle safety issues faster.
Inspecting the power grid and detecting safety hazards often requires workers to work in hazardous environments. Using drones/UAVs and AI allows this to be done remotely and reduces the risk to workers. Drones/UAVs have the ability to fly to difficult to reach or hazardous areas.
Using AI enables more automated and accurate processing and analysis of images/videos collected from drones/UAVs. This helps to reduce human errors and enhance the ability to detect potential risks effectively. Drone/UAV technology and AI can be expanded to a wide range of areas and regions, from urban to rural areas, enhancing the ability to detect and respond to safety issues on the global power grid.
Drones are used to perform comprehensive monitoring tasks on the power grid, thereby detecting weaknesses, damage, or potential risks on power lines, substations, and electrical works. AI combined with drones helps to quickly detect damage after natural disasters such as storms, earthquakes, landslides, providing management agencies with complete and accurate information to deploy timely remedial measures. Autonomous flight programming combined with AI can perform inspections, assess the condition of power poles, measure parameters and environmental data to detect potential problems early.
In addition, with the increasingly rapid development of technology, new AI models and deep learning algorithms are increasingly improving in accuracy, while communication with drones/UAVs through IoT systems is increasingly developing and becoming more complete, with high automation. This ensures that research and construction of new systems on new technology platforms, improving accuracy, automation and at the same time mastering technology for development is extremely necessary. Deploying these drones to collect image/video data and applying AI is not only easy but also effective in improving the management process and maintaining grid safety.
With the characteristics of the distribution grid, the attributes and objects are different from previous studies of the units, the research group set the task of building an IoT application combined with an AI model to detect abnormalities on the distribution grid.
In particular, focusing on automation in setting up autonomous flight missions and transmitting collected data to the server so that the AI system can automatically analyze abnormalities on the distribution grid. Applying AI to identify abnormal objects on the grid also opens up many new research directions and applications for AI in the electricity industry. This not only contributes to the development of AI and technology but also creates opportunities for AI research in the electricity industry in the future.
Tan Nguyen
Source: https://baoquangtri.vn/canh-bao-nguy-co-mat-an-toan-luoi-dien-bang-tri-tue-nhan-tao-187453.htm
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