Category: Autonomous Systems

AI for Autonomous Drones

AI for autonomous drones refers to the use of artificial intelligence to allow drones to operate without direct human control. By processing data from sensors and cameras, AI enables drones to make decisions such as navigating obstacles, choosing flight paths, and responding to changing environments. This technology helps drones perform complex tasks safely and efficiently,…

AI for Environmental Monitoring

AI for Environmental Monitoring refers to the use of artificial intelligence technologies to observe, analyse and predict changes in the natural environment. This can involve processing large amounts of data from sensors, satellites or cameras to track pollution, wildlife, weather patterns or deforestation. AI helps make sense of complex data quickly, supporting better decision-making for…

AI for Smart Manufacturing

AI for smart manufacturing refers to the use of artificial intelligence technologies to improve efficiency, quality, and flexibility in factories and production lines. By analysing data from machines and sensors, AI can predict equipment failures, optimise production schedules, and help workers make better decisions. This approach helps manufacturers save time, reduce costs, and produce goods…

AI for Automated Negotiation

AI for Automated Negotiation refers to the use of artificial intelligence systems to conduct or assist in negotiation processes. These systems can analyse offers, counter-offers, and preferences to reach agreements that benefit all parties involved. By processing large amounts of data and learning from past negotiations, AI can help make quicker and more objective decisions,…

Edge AI for Industrial IoT

Edge AI for Industrial IoT refers to using artificial intelligence directly on devices and sensors at industrial sites, rather than sending all data to a central server or cloud. This allows machines to analyse information and make decisions instantly, reducing delays and often improving privacy. It is especially useful in factories, warehouses, and energy plants…

AI for Smart Cities

AI for Smart Cities refers to the use of artificial intelligence technologies to improve how cities operate and serve their residents. AI systems can help manage traffic, save energy, reduce pollution, and make public services more efficient. By analysing data from sensors, cameras, and other sources, AI can help city officials make better decisions and…

RL for Industrial Process Optimisation

RL for Industrial Process Optimisation refers to the use of reinforcement learning, a type of machine learning, to improve and control industrial processes. The goal is to make systems like manufacturing lines, chemical plants or energy grids work more efficiently by automatically adjusting settings based on feedback. This involves training algorithms to take actions that…

RL for Autonomous Vehicles

RL for Autonomous Vehicles refers to the use of reinforcement learning, a type of machine learning where computers learn by trial and error, to help vehicles drive themselves. The system receives feedback from its environment and improves its driving by learning from rewards or penalties. This approach allows autonomous vehicles to adapt their driving strategies…

RL for Real-World Robotics

Reinforcement Learning (RL) for Real-World Robotics is a branch of artificial intelligence that teaches robots to learn from their own experiences through trial and error. Instead of following pre-programmed instructions, robots use RL to figure out the best way to complete tasks by receiving feedback based on their actions. This approach allows robots to adapt…