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By KTP Radhika
Chennai-based Greenvironment is providing smart AI-based technologies for managing water and treating wastewater in commercial establishments and residential communities.
India is in the grip of acute water scarcity. According to NITI Aayog’s Composite Water Management Index, 40 per cent of India's population will have no access to drinking water by 2030. The report states that per person disease burden due to unsafe water and sanitation was 40 per cent higher in Indian than China and 12 times higher than in Sri Lanka in 2016. More than 70 per cent of sewage generated in India goes untreated.
“With the country generating huge amounts of wastewater annually, mismanagement of wastewater, which also contaminates groundwater; lack of liquid waste management; poor sanitation condition and poor hygiene habits have contributed to a significant portion of the population suffering from water-borne diseases,” states Dr Rajiv Kumar, Vice-chairman Niti Aayog, in the Composite Water Management Index 2.0 released last year.
Chennai-based firm Greenvironment is trying to address this problem using artificial intelligence. Founded in 2012, Greenvironment offers solutions such as design, execution and real-time monitoring of sewage treatment plants, rainwater harvesting, effluent treatment and ultrafiltration for commercial as well as residential buildings. “Water treatment plants in buildings and businesses are dynamic systems that require adjustments to be made on the fly for smooth running. For this, access to real-time data is absolutely essential,” says Varun Sridharan, Founder of Greenvironment.
“However, at present, operational decision-making at most plants remains largely on after-the-fact information. Moreover, the pressure to keep running costs low forces many customers to rely on unskilled operators for plant management, resulting in unreliable and sub-optimal performance,” he says. The company has developed an AI-based Real-Time Monitoring (RTM) system to address these problems.
Greenviornment’s RTM system comprises a full array of smart sensors. The sensors collect data over a cloud infrastructure on the quality, flow, energy and other environmental indicators from RO plants, water treatment plants, sewage treatment plants, and cooling towers. The real-time data from these utilities are visualized on a cloud-based analytics platform to predict the performance, faults and provide troubleshooting insights for the operations team. Our RTM Analytics dashboard explains water usage patterns in the building, efficiency metrics of the utilities in terms of treatment, filtration and disinfection, the performance of automated systems and lifecycle support.
“By implementing this solution, establishments will have reliable data to make appropriate decisions on water management and achieve fast recovery measures in case operational process stability is lost, eventually benefiting in long term to manage public health using data,” says Sridharan. The company also has built an AI-based smart assistant. Using past data, this smart bot will automatically alert and suggest resolutions for most frequently occurring issues in water utilities. “This is helping us to scale our solutions quickly and reduce manual intervention,” says Sridharan.
“The RTM system delivers a host of benefits”, states Sridharan. The system provides reliable data to make appropriate decisions on water, energy and environmental management while reducing the water consumption and thereby the cost. The system also provides fact recovery measures in case operational process stability is lost. The solution saves energy and chemical costs while reducing the skilled manpower requirement. Currently, the company has customers across various segments like hospitals, hotels, residential communities, IT parks, shopping malls and industries.
Greenvironment is also developing image processing techniques for their AI solution. “We are trying to monitor treatment efficiencies of water treatment plants, which will ensure good quality of treated water. This will help us to scale our solutions quickly and reduce manual intervention,” Sridharan assures.
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