Kayal
Problem: Keeping urban waterways clean is essential for healthy cities and also preventing ocean plastic pollution. However, the current global methods for waterway maintenance are labour intensive, inefficient and don't scale.
Solution: We’re automating waterway maintenance with AI and drone technology. We are building all-electric, autonomous aquadrones that collect floating debris and remove weed using computer vision. They also function as mobile data acquisition platforms, tracking waste aggregation trends while recording water and air quality data.
Impact in Bangladesh: Cities in Bangladesh are rapidly expanding. Consequently, urban waterways Bangladeshi cities are being destroyed by solid waste dumping, unauthorized land filling and construction, etc. Our drones make waterway cleaning cheaper, more effective and more efficient. Further, data acquisition helps measure chemical discharge, intensity of pollution, canal depth, water carrying capacity etc. informing sound intervention by authorities.
Dhaka has lost up to 50 canals in the last 30 years - due to severe solid waste pollution and encroachment. This has led to the following issues: 'a collapse of the natural drainage system leading to urban flooding in normal monsoon, spread of skin and intestinal diseases among the urban poor who use canal water in the absence of access to clean water, breeding of mosquitoes leading to water borne diseases like malaria and diarrhea in stagnant canals, as well as environmental impacts such as loss of landscape, decreasing water quality, reduced ecological connectivity, and decline of ground water aquifer recharge'' (Environmental Justice Atlas 2015). This is not just the story of Dhaka, this is the story of nearly every Bangladeshi city.
Dhaka is home to 18 million people. They are one of the worst affected urban populations in the world when it comes to flooding. Korail slum in Dhaka spreads over 50 acres and houses more than 50,000 people - and during monsoon the entire slum can be found underwater. Bangladesh is home to 50 million urban residents of whom about 20 percent live below poverty line.
Contributing factors: population rise, unplanned urban development.
We serve two vulnerable segments of the population:
- Slum communities in densely populated urban areas, particularly those lining waterways
- Coastal communities dependent on the marine ecosystem for livelihood and food
Urban waterways in developing countries are narrow, shallow, and heavily polluted. To perform cleaning in such conditions, the device needs to be compact but capable of heavy-duty operation and offer a large payload. Further, the pricing must be suitable for developing countries. Our trash skimmer encompasses all these considerations and will have 10x the carrying capacity of comparable solutions in this space.
Further, we have observed and interviewed a large number of cleaners, who also live in the same slums. Our interaction with the cleaners led us to decide that we will primarily sell human operated versions of our trash skimmers in regions where there is a shortage of jobs. Thus, we will not cause a loss of employment: some of the existing cleaners will be retrained as operators while others will be absorbed by the ecosystem assigned to safely dispose of the collected waste.
Our solution will ensure that the waterways close to slums are clean, flowing, and free of larval breeding locations.
Hardware
Our primary product is an intelligent trash skimming aqua drone that uses computer vision to scavenge for floating waste and aquatic weed. Currently, we finished the design and engineering work and started manufacturing the product. We expect to complete the work in 4 months. We launch as a human operated drone in South Asian market for reasons listed under the previous question.
Key design features:
- All-electric and highly energy efficient
- Superior hydro dynamic performance
- A novel conveyor manipulation system for independent collection and disposal of trash
- Small form factor and lightweight
Technical specifications:
- Dimensions: 3 m (length) x 2 m (width) x 0.75 m (height)
- No-load weight: 400 kg
- Average speed: 10 km/h
- Run time: 8 hours
- Payload volume: 1,000 liters
- Payload weight: 200 kg
- On-board sensors: RGB camera, GPS, underwater sonar, depth, temperature and pH-level sensors
- On-board computer: Jetson TX2
Software
In parallel, we are working on the robotics software platform using a smaller, proof of concept drone we have built.
The test drone's current workflow is:
- An operator defines a target search area with GPS points
- The aqua drone then scavenges for floating waste using computer vision within that geo-fence. We use k-means clustering and Speeded Up Robust Features for identifying floating debris and optical flow based tracking to continuously track and collect the waste
- The drone returns to the starting position once it completes the work.
- The operator can view the on-board camera's live stream and also intervene at any point during the mission via a base station (either mobile phone or a laptop) that is linked with the aqua drone.
Notes: The communication is via 3G/4G (any distance, provided both the robot and the base station have strong GSM connections) or WiFi (100 meter radius with line of sight). Additionally, the drone also supports Radio Control (1000 meter radius with line of sight). The test drone is currently trialing alongside Colombo's canal cleaners.
- Reduce economic vulnerability and lower barriers to global participation and inclusion, including expanding access to information, internet, and digital literacy
- Environment
- Technology
- Prototype