Autonomous Drones Monitoring Singapore’s Reservoirs
Smart water management systems can provide water utilities with real-time, automated data for use in resolving water challenges. Read how Singapore is deploying autonomous drones to monitor its reservoirs.
Artificial intelligence (AI) is intelligence exhibited by machines or computers, allowing them to perform tasks such as understanding, learning, reasoning, planning, and more. In its current application, AI systems can rationally solve complex problems, predict outcomes, and act in real-world situations to achieve goals. The spectrum of AI is expanding and includes automated intelligence systems that take repeated, labour-intensive tasks requiring intelligence, and automatically completes them and helping people perform tasks more quickly and better use the information collected.
In the context of water resources management, AI and associated sensors and other data-driven technologies can continuously collect data on different phases in the water supply and demand, including water supply monitoring and management, water quality monitoring, and harmful algal blooms and monitoring.
Singapore’s autonomous drones monitoring reservoirs
Singapore’s Public Utilities Board (PUB) has deployed autonomous drones to manage aquatic plant growth and monitor reservoir activities. The Beyond Visual Line of Sight (BVLOS) drones will begin monitoring six reservoirs across Singapore, with each drone equipped with remote sensing systems and a camera for near real-team video analytics. Starting with one drone at MacRitchie and another at Marina reservoir, PUB will progressively deploy one drone each to the four other reservoirs (Serangoon, Kranji, Lower Seletar, and Lower Peirce) later this year.
The drones at MacRitchie and Marina are housed in an automated pod and are capable of taking off and landing autonomously. The flights are pre-programmed and monitored remotely by an operator. The drones will conduct daily patrols to monitor water quality, detect excessive growth of aquatic plants and algal blooms, and collect data on water activities, such as fishing and paddling, in and around the reservoirs’ edge. Specifically:
- Monitoring water quality: Using the drone’s water quality remote sensing system, the drone will gather data on turbidity and algae concentration, which provides a good correlation to actual water quality. If necessary, PUB officers will collect water samples on-site for further analysis
- Monitoring aquatic plant growth: A video analytics algorithm is used to identify aquatic plant overgrowth in the reservoir via the drone camera’s live video feed. The algorithm can differentiate between plants above the surface and plants that are submerged
- Monitoring water activities: The drone’s live video feed will monitor water activities, with a video analytics algorithm flagging potential concerns, such as anglers fishing in non-designated areas or overcrowding of vessels in a particular area. If any concerns arise, a message will be sent to a dedicated Telegram channel that officers can access via their mobile phones, allowing them to respond to issues quickly
Overall, 7,200 hours of staff time is normally used per annum to undertake these tasks. By utilising the BVLOS drones, around 5,000 hours of staff time will be saved, allowing the utility to redirect its staff to other works.
The take-out
Deploying autonomous systems means more staff time can be dedicated to other tasks.
Join the conversation on the following LinkedIn groups: Urban Water Security, Our Future Water, Circular Water Economy, Blue-Green Infrastructure, Nature-Based Solutions, and Urban and Regional Futures
