AI Enhances Safety for Autonomous Drone Aircraft Traffic

Posted by: Prof. P. Sandhiyadevi

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AI Enhances Safety for Autonomous Drone Aircraft Traffic

In recent days AI gets more impact in our day todays life. Autonomous vehicle role in our environment getting increased in recent days. Usage of autonomous drone in various fields like surveillance, image capturing etc. probably getting increased. All of these AI based applications will improve the efficiency, accuracy and time reduction. Apart from all the advantages of using AI there will be more challenges in safety side on both manned and Unmanned Vehicle. To address these challenges researchers had many research on safety for autonomous drone and also to control the traffic on unmanned vehicle.


Safety challenges in Autonomous Drone

Before entering into the AI role in autonomous drone traffic control we should recognize the challenges in autonomous drone. Basically, Unmanned drone will work on small airspace and also in various dynamic environment like different weather conditions, various obstacles which makes difficult to navigate.


Moreover, by increasing the number of drones in commercial and industrial purpose also one of the reasons for airspace traffic and collisions. It is necessary to build the system to monitor and control the operations of autonomous drone. This system will help to increase the safety measures and reduce the risk for people and also property.


Role of AI in enhancing Safety

AI playing vital role in almost all the fields. AI gives multiple approach to address the safety challenges in unmanned drone traffic in airspace. By introducing the machine learning and deep learning algorithms AI models can able to improve their real time data analysis, various feature prediction, obstacle prediction can avoid the collision and also enhance the overall situational awareness for unmanned drone operators and traffic control system.


Along with these features, AI based unmanned drones can able adjust the routes based on the environment conditions. AI based weather prediction infused systems can able to predict the weather conditions for drone operations. These features can help the drones to operate in safer routes and can help to navigate in safer airspace.


Traffic management and Routing

One of the main roles of AI is reducing the collision by increasing the traffic management system and routing. These Machine learning algorithms and deep learning algorithms can able to analyze the huge amount of data, predicting weather conditions and because of increasing flight route AI based management system can able to identify these routes which helps to reduce the collisions and airspace congestions.


Collision Avoidance system

Collision avoidance system plays a vital role in unmanned drone system and also manned aircraft. AI based collision avoidance system uses sensors, radars and cameras to detect the obstacles and nearby aircrafts, these utilities can help for continuous monitoring in real time for collision avoidance. Machine learning and deep learning algorithms plays a vital role in detecting the obstacles and detecting flight routes, weather prediction.


Autonomous Decision Making

AI based autonomous drone can able to take decision in critical situations and predictive modelling. By infusing these AI based system can able to control the traffic in airspace, drones can able take decisions suddenly in critical situations like changing in wind speed, unexpected airspace restrictions without human interruptions.


Regulatory Frame works

Regulatory frame works can play an important role in framing guidelines and standards in integrating AI technology with unmanned drones. By involvement of industry experts and technology providers makes the frame work of drone to meet all safety measures and standards.


Industry Collaboration

Industry collaboration is most important for new innovation and development of AI solutions for unmanned drone safety purpose. Due to industry collaboration, we can able to share more data, able to analyze data, due to continuous practice and lessons we can able to address more challenges and can able to develop AI integrated drones more effectively.


Continuous Improvement

AI technology needs continuous improvement and iterations in order to improve the efficiency and safety measures. By doing continuous research and development, due to testing and validation stakeholders can move forward in emerging threats and challenges in autonomous drone aircraft traffic.


In this modern technology world, it is more important to introduce this AI based technology in various fields. In AI, introducing the efficient algorithm is most important in order to achieve high efficiency models. In this unmanned airspace drone was integrated with AI in order to ensure the collision avoidance and obstacles detection without human interruption was discussed. By doing continuous research we able to develop better efficiency models.



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