Researchers at the Indian Institute of Technology Madras (IIT-Madras) have developed a robot, HomoSEP, to eliminate manual scavenging in the country. Septic tanks are poisonous environments, filled with semi-solid and semi-fluid human faecal material that make up about two-thirds of the tank. Hundreds of deaths are reported every year across India, due to manual scavenging in these tanks, despite bans and prohibitory orders.
The HomoSEP robot can homogenise hard sludge in the tank through a custom-developed rotary blade mechanism and pump the tanking slurry using an integrated suction mechanism. Sanitation workers will be able to operate the HomoSEP on their own, after being provided with the relevant training and appropriate guidance along with necessary safety measures. Safety plays a vital role in this whole procedure, starting with the design of HomoSEP itself, IIT-Madras stated in a recent statement.
The Institute has been developing the technology for several years. Since the first proof-of-concept, the research team has made some significant innovations, including improving the blade design through extensive simulation and achieving miniaturisation for better portability. Moreover, they integrated the product with a tractor, enabling it to reach remote locations.
Ten units will be deployed across the state of Tamil Nadu, and the Institute is also considering areas in Gujarat and Maharashtra. The researchers have been in contact with sanitation workers to identify locations. So far, two HomoSEP units have been distributed to self-help groups. An official said that the team hopes to leverage support from government channels to mass-produce and distribute the solution on a much larger scale throughout the country by next year.
The Institute has been developing several technology-based solutions to combat a variety of societal challenges. Last month, IIT-Madras developed a machine-learning algorithm to save wildlife from illegal poaching, logging, and fishing. The CombSGPO (Combined Security Game Policy Optimisation) algorithm performs strategic resource allocation and patrolling in green security domains to protect animals.
As reported on OpenGov Asia, the research team found that the combined and coordinated use of forest rangers and surveillance drones, referred to as resources, was a good way to protect wildlife from poaching. As the resources are limited, the algorithm provides highly efficient, scalable strategies. After the extent of resources has been identified, the algorithm handles resource allocation and strategises patrolling. It uses data from the animal population in the conserved area and assumes that poachers are aware of the patrolling being done at various sites. The drones have object detectors mounted on them to signal and communicate with each other as well as the human patrollers.
The algorithm works on a game theory-based model created by the researchers. Game theory is a theoretical framework for conceiving social situations among competing players. In the context of wildlife protection, game theory pertains to predicting the areas where poaching may take place. These predictions are based on the history of poaching incidents and interactions between poachers and defenders. The game model and the kind of resources researchers used to simulate such a ‘poaching game’ between the defender (forest rangers and drones) and attackers (poachers) are based on the widely-studied Stackelberg Security Game Model and are linked to drones that have already been deployed in Africa to stop elephant and rhino poaching.