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How might we deploy a cost-effective solution to autonomously inspect our drainage network to identify drain defects and map out the drain alignment/dimension?
Challenge Owner
In Singapore, rainwater is collected through 8,000 km of drains, canals and rivers. As part of the maintenance regime in PUB, public drains are inspected regularly (typically once every 5 years) for defects and subsequent rectification to ensure that the drainage network is structurally safe and functional. While we would like to increase the frequency of inspection, it is not sustainable to do so with current methods.
Currently, PUB conducts manual inspections for most open and closed drains, which is labour intensive. In addition, closed drains with confined space pose potential atmospheric and physical hazards. Man-entry into closed drains is potentially hazardous and requires precautions, which reduces inspection efficiency and increases costs.
Recently, PUB has deployed autonomous drones that can navigate in GPS-denied and unilluminated closed drains to provide visual images of the drains without requiring man-entry. This has improved productivity by reducing the time and manpower required and enhanced safety by eliminating the need to access and work in a confined space environment. However, the current drone solution can only be used to inspect drains that are more than 2m wide. It is unable to inspect smaller drains (i.e., less than 2m wide), which form a significant portion of the drainage inventory, due to the bigger drone size required to house a battery of sufficient capacity.
During the deployment of drones in drains more than 2m wide, there are also several challenges encountered due to their relatively big size and water-phobic nature. For instance, obstruction due to underground services or animals makes it difficult for the drone to manoeuvre around. As the drone is water-phobic, the drone operator needs to take additional measures (i.e. manually follow the drone) when flying the drone in a partially submerged drain to prevent it from coming into contact with water.
In addition, beyond visual information, we are seeking solutions that automate the detection of defects with high accuracy and pinpoint exactly where such defects are within the network. We also require the solution to map out the drain alignment and dimensions into a geospatial database as it performs the inspection. This will help to automatically update the drainage records to confirm as-built drawings and provide new digital mapping data, particularly for older drains.
While PUB has deployed autonomous drones to replace man-entry for a small number of closed-drain inspections, we are open to both drone and non-drone solutions that can achieve the above.
We are interested in solutions that can autonomously:
The solution shall be:
The inspection and data processing methods, e.g. data transfer and report generation should adopt innovative methods that require minimal manual interventions in order to achieve smarter operations
In addition, the need for personnel to follow the autonomous robot/drone during the inspection to retrieve it in the event of failure would be a strain on manpower resources and is disadvantageous
A cost-effective site-tested prototype system that can autonomously inspect drains of various types and dimensions, automatically identify drain defects in real-time during an inspection and map out the drain alignment and dimensions to an accuracy of +/- 0.1m for horizontal and vertical displacement into a geospatial database.
If the pilot is successful, the solution would be provided to PUB through a service model where the equipment is owned, operated, and maintained by the company.
Challenge Owner
In Singapore, rainwater is collected through 8,000 km of drains, canals and rivers. As part of the maintenance regime in PUB, public drains are inspected regularly (typically once every 5 years) for defects and subsequent rectification to ensure that the drainage network is structurally safe and functional. While we would like to increase the frequency of inspection, it is not sustainable to do so with current methods.
Currently, PUB conducts manual inspections for most open and closed drains, which is labour intensive. In addition, closed drains with confined space pose potential atmospheric and physical hazards. Man-entry into closed drains is potentially hazardous and requires precautions, which reduces inspection efficiency and increases costs.
Recently, PUB has deployed autonomous drones that can navigate in GPS-denied and unilluminated closed drains to provide visual images of the drains without requiring man-entry. This has improved productivity by reducing the time and manpower required and enhanced safety by eliminating the need to access and work in a confined space environment. However, the current drone solution can only be used to inspect drains that are more than 2m wide. It is unable to inspect smaller drains (i.e., less than 2m wide), which form a significant portion of the drainage inventory, due to the bigger drone size required to house a battery of sufficient capacity.
During the deployment of drones in drains more than 2m wide, there are also several challenges encountered due to their relatively big size and water-phobic nature. For instance, obstruction due to underground services or animals makes it difficult for the drone to manoeuvre around. As the drone is water-phobic, the drone operator needs to take additional measures (i.e. manually follow the drone) when flying the drone in a partially submerged drain to prevent it from coming into contact with water.
In addition, beyond visual information, we are seeking solutions that automate the detection of defects with high accuracy and pinpoint exactly where such defects are within the network. We also require the solution to map out the drain alignment and dimensions into a geospatial database as it performs the inspection. This will help to automatically update the drainage records to confirm as-built drawings and provide new digital mapping data, particularly for older drains.
While PUB has deployed autonomous drones to replace man-entry for a small number of closed-drain inspections, we are open to both drone and non-drone solutions that can achieve the above.
We are interested in solutions that can autonomously:
The solution shall be:
The inspection and data processing methods, e.g. data transfer and report generation should adopt innovative methods that require minimal manual interventions in order to achieve smarter operations
In addition, the need for personnel to follow the autonomous robot/drone during the inspection to retrieve it in the event of failure would be a strain on manpower resources and is disadvantageous
A cost-effective site-tested prototype system that can autonomously inspect drains of various types and dimensions, automatically identify drain defects in real-time during an inspection and map out the drain alignment and dimensions to an accuracy of +/- 0.1m for horizontal and vertical displacement into a geospatial database.
If the pilot is successful, the solution would be provided to PUB through a service model where the equipment is owned, operated, and maintained by the company.
