Сomputer Vision Software for Drones in Utility Sector
Surveillance drones are becoming more common today. This reduces errors, is cost effective, improves accuracy and reduces workload. But drones are not the only technology: the use of machine learning + computer vision can significantly improve the accuracy and efficiency of terrain monitoring.
UAVs (Unmanned Aerial Vehicles) can be used in monitoring and maintenance of all types of power & utilities production facilities, and thanks to special sensors, they not only capture the current state but also provide analysis of numerous factors influencing the operation of the facility.
Area monitoring is an important part of work for any power & utility business because prevention of accidents is often much more cost-effective than management of the problems. The areas that power & utility companies have to monitor are in most cases spread all over huge areas with numerous hard-to-reach objects. More than that, the inspection of some areas can be risky and dangerous for people, and before drones were only monitored with the help of planes and helicopters.
But drones are not a sole technology: using Machine Learning + Computer Vision can significantly improve the accuracy and efficiency of area monitoring. Machine learning presupposes that algorithms are trained to solve tasks independently based on the analysis of provided examples of similar solutions. Thus, if trained to find suspicious objects near power grids, AI-powered drones can do it automatically reducing the workload of employees.
For these reasons, drones are getting more and more widespread today for area monitoring. The benefits are really obvious:
Cost-effectiveness. Area monitoring with the help of drones is cost-effective compared to any human work. Using drones and video analytics of the footage it is possible to monitor large areas effortlessly and promptly with minimal human involvement.
Reduced amount of errors. Using AI gives companies a chance to avoid errors because of a lack of concentration or inattentiveness. More than that, image analysis performed by a human being decreases with the hours spent at work because of exhaustion. Whereas machines only get smarter by analyzing more mages.
The increasing level of accuracy. As mentioned in the previous item, using video analytics ( Machine Learning + Computer Vision) for the image analysis presupposes that the quality of this analysis will be increasing with the amount of data that is fed into the system. Data in this particular business case means labeled images.
Reduced workloadon the employees of power & utility companies thanks to the automation of the repetitive tasks.
Lower risks for employees when monitoring hard-to-reach areas.
Several Popular Use Cases of AI in Utility & Power Sector
Monitoring forestry is one of the most challenging tasks for the power industry. The contact between tree branches and power lines is the reason for the power outage and most companies naturally avoid this. Reducing the risk of the contact between vegetation and power lines could decrease costs for the utility & power industry immensely.
Improperly Placed Rubbish
Rubbish placed near important power & utility objects can be a real threat. It can be easily inflammable, toxic, or increase the risks of accidents for employees. Spotting improperly placed rubbish before any accidents mean decreasing risks for the organization.
Pipeline Construction Monitoring
During the construction of the pipelines, it is important to monitor the area because of the potential threats of intrusion, fires, floods. Drones powered with AI help to monitor pipeline construction areas even in the most hard-to-reach areas.
The power & utility area is attractive for intruders who aim to take profit from the expensive materials. Sometimes there are vandals who invade the perimeter without permission. A flying drone, can immediately detect intruders and send an alert to security personnel.
AI-powered Drones are applicable in numerous industries today. Here are some use cases from other industries:
Logistics. Transport infrastructure monitoring ( roads in the process of construction)
Real estate. objects monitoring during construction. Using drones for these purposes allows us to perform quality control and analyze the progress of the construction.
Telco. Monitoring of telecommunication installations
Agriculture. Сrops conditions monitoring, disease hallmarks monitoring, fertilization needs analysis. All these goals can be achieved remotely using AI-powered drones.
Insurance. Using drones it is also possible to eliminate numerous conflicts with farmers in case of insurance claims.