Solar panels require sunlight to operate efficiently; however, in several regions of India, dust, bird droppings, and pollution quickly cover their surface, obstructing light penetration. Maintaining the cleanliness of thousands of panels in vast solar farms located in arid and dusty areas is a constant challenge. Contamination reduces electricity generation, and regular cleaning demands significant amounts of water and a large workforce.
Researchers from the National Institute of Technology (NIT) in Rourkela have created an artificial intelligence-based system that makes this process more targeted. This system can monitor the condition of solar panels, determine exactly which ones need cleaning, and focus efforts only on those specific zones. This potentially helps solar power plants consume less water and labor while maintaining high panel efficiency.
The technology was developed by Professor Arun Kumar, Assistant Professor, Professor Bibhudatta Sahu, and graduate researchers Dr. Lopamudra Hote and Dr. Biraj Prasad Nayak from the Department of Computer Science and Engineering at NIT Rourkela. The team received an Indian patent titled 'Autonomous system and method for monitoring and cleaning a solar power station based on federated learning.' The problem they are solving is becoming increasingly relevant as the share of solar energy in India grows.
According to the researchers, solar farms in dry and dusty locations can lose up to 40% of their energy output due to the accumulation of dust, bird droppings, industrial pollutants, and other particles on the panels. Regular cleaning of these panels involves several difficulties, as many existing systems heavily rely on manual labor and water. Furthermore, solar farms often clean panels on a fixed schedule, regardless of whether each panel needs cleaning, leading to wasted time, money, and water on already functional panels.
The NIT Rourkela team developed a system that uses artificial intelligence to continuously check the condition of solar panels. It is capable of detecting faults, analyzing real-time conditions, and recommending which panels truly require attention. Thus, instead of cleaning the entire solar farm at set intervals, operators can focus exclusively on the panels that need maintenance.
The system utilizes an AI type known as Federated Learning (FL). Simply put, Federated Learning allows various devices or systems to learn from data without sending all the raw information to a single central server. Currently, the technology has been tested in simulations and is at Technology Readiness Level 3 (TRL-3), meaning the basic concept has been demonstrated as a proof-of-concept in controlled experimental settings.
Another important aspect of the system is its approach to data processing. Many traditional AI systems collect raw information from different locations and transmit it to a central server for processing. The NIT Rourkela system follows a different path by using the Federated Learning architecture, ensuring privacy by exchanging encrypted data instead of raw operational data. The researchers note that this approach reduces concerns regarding data privacy, cybersecurity, and required internet bandwidth, while also simplifying the scaling of the technology to larger solar installations.
Commenting on this technology, Dr. Arun Kumar, Assistant Professor at NIT Rourkela, stated: 'The patented system integrates federated learning, edge computing, artificial intelligence, autonomous cleaning, and predictive maintenance into a single integrated sandbox platform.' He added that features such as intelligent real-time operation, automatic fault detection, selective cleaning, reduced water consumption, and lower maintenance costs make the system unique.
The researchers believe the system can be used in various types of solar installations. These include large-scale utility solar power plants, floating solar farms, rooftop solar systems, industrial solar parks, smart city energy infrastructure, defense facilities, and remote off-grid renewable energy sources. This means the technology can ultimately benefit both large energy producers and small renewable energy grids aiming to reduce the effort and costs associated with solar panel maintenance.
The researchers also believe that this technology can significantly reduce the cost of solar panel maintenance. Professor Bibhudatta Sahu from NIT Rourkela asserts that many existing solutions have high initial costs and offer a limited level of intelligence. Their system, he says, combines several AI-based functions, allowing monitoring, decision-making, and cleaning to occur more automatically.
He noted: 'While current market solutions suffer from high capital expenditure and limited intelligence, our developed system integrates advanced AI capabilities for autonomous operation.' After development for large-scale field use, the researchers expect the system to offer its functionalities at approximately 10% of the cost of existing systems.
Currently, the system has been tested in simulations. The team's next step is to create a physical hardware prototype and connect it to Internet of Things (IoT) sensors. These sensors will help collect information directly from solar installations and allow researchers to test the system outside the laboratory. The team plans to move from simulation-based testing to pilot projects in real-world conditions. They also intend to collaborate with government agencies and industry partners to support field trials and subsequent technology transfer for broader application. Future versions of the system may include drones for panel inspection, multiple cooperating cleaning machines, and AI tools capable of predicting the approximate energy output of the solar power station.
India is expanding its solar energy infrastructure under the National Solar Mission and broader net-zero emission goals. As new solar farms are built, maintaining their efficiency without excessive consumption of water, labor, and money will become a crucial part of the task. The NIT Rourkela team's system aims to make this maintenance smarter by checking panels that need attention and concentrating cleaning where it is truly necessary. If the technology successfully passes real-world tests and is implemented on a large scale, it can help solar power plants generate more energy while using fewer resources.
An electric scooter battery lasts for about five years, providing daily rides. However, when the battery's health drops below 70%, most people consider it ordinary trash. Industry, on the other hand, sees it as a treasure trove of critical minerals. Currently, a spent battery ceases to be just an automotive component and becomes part of a grand industrial transition.
As the adoption of electric vehicles accelerates in the country, the fate of these batteries will determine whether India becomes a self-sufficient producer or replaces its dependence on crude oil imports with a dependence on critical mineral imports. India aims to achieve sales of 30 million electric vehicles by 2032. According to NITI Aayog estimates, approximately 128 GWh of battery waste will be generated in India by the end of the decade, with the electric vehicle segment accounting for nearly half of this volume. Thus, what appears to be waste is actually a concentrated urban mine.
End-of-life lithium-ion batteries contain all the necessary materials to create the next generation of energy storage systems. The projected 128 GWh of waste could potentially yield a colossal 17,500 tons of lithium, 22,600 tons of nickel, 2,600 tons of cobalt, and 141,800 tons of graphite.
For a country with limited domestic reserves, mining these minerals is a macroeconomic necessity. According to a Rocky Mountain Institute report, the battery circular economy represents a $9 billion market opportunity for India. By 2050, a robust domestic recycling infrastructure could meet over 40% of the country's domestic needs for lithium, nickel, and cobalt, protecting production from global commodity market volatility.
Extracting critical minerals is far more complex than simply dismantling a battery. Each battery varies in chemistry, design, physical condition, and residual charge, making safe handling the first engineering challenge. After controlled discharge, batteries are mechanically dismantled and crushed in a controlled environment to separate plastic, copper, and aluminum foil.
The result of the crushing process is a dark fine powder known as 'black mass,' which contains concentrated active metals driving the energy transition. Advanced purification methods allow for the extraction of lithium, nickel, cobalt, and graphite as metal or salts with a recovery efficiency exceeding 90%. Ultimately, the metals in the battery packs remain metals and can be transformed into various forms of these metals. Purified metals can be reused in various production streams, including batteries, through recycling.
The real economic value lies in recycling the black mass into metals or salts that industry can use, not in producing the black mass itself. Until recently, black mass was largely exported, effectively transferring significant value abroad. Domestic recycling retains value within the country's own production ecosystem and strengthens the battery manufacturing, chemical, and advanced materials industries.
Operating a recycling facility demonstrates that a metallurgical approach alone is insufficient for commercial success; process design is also crucial. Multi-stage chemical extraction technologies increase reagent consumption, waste generation, and operating costs. As Lithium Iron Phosphate (LFP) becomes the preferred chemistry, commercially viable recycling will depend on chemistry-agnostic technologies that simplify the process while operating efficiently at scale.
Despite technical success in recovering critical minerals, LFP batteries present a commercial challenge. Unlike premium Nickel-Manganese-Cobalt (NMC) batteries saturated with high-value metals, LFP batteries do not contain nickel or cobalt. Although lithium, iron, and phosphorus can be extracted, current raw material prices do not cover processing costs. The science of recycling is sound, but the economics can be harsh. If left entirely to the free market, recyclers will naturally favor NMC batteries and abandon LFP, leading to piles of untreated toxic waste.
To prevent LFP packs from becoming a devalued asset, the industry requires Viability Gap Funding (VGF) grants or chemistry-specific differentiated incentives to make processing low-value chemistries financially sustainable.
Securing feedstock is a huge hurdle. Approximately 70%–90% of India's battery waste disappears into the unregulated informal sector, where unsafe scavenging causes environmental damage and massive material loss. The Battery Waste Management Rules (BWMR) 2022 timely introduced Extended Producer Responsibility (EPR) to channel waste to recyclers, but compliance with these rules remains critical. Ensuring traceability throughout the entire life cycle of a battery until its decommissioning can guarantee that batteries remain within the formal circular economy.
Ultimately, transforming battery waste into strategic resources is the defining industrial challenge of the electric mobility era. Batteries are a source of raw materials underpinning India's transition to clean energy and its industrial competitiveness. By scaling up advanced purification, supporting economically challenging chemistries like LFP, and strengthening EPR compliance and battery traceability, battery recycling will evolve into a strategic industrial opportunity.
Regardless of whether it is the rainy season or hot weather, snakes often appear around houses. If you feel that snakes suddenly enter your home, this is not always the case. Often, snakes do not penetrate a dwelling without reason; rather, some minor mistakes in the kitchen create conditions for their appearance both outside and inside.
In fact, snakes are not directly attracted by food. However, certain items in the kitchen attract mice, insects, and other small animals that are prey for snakes. If there are items stored in your kitchen that can become food for rodents and insects, the appearance of snakes in the kitchen becomes likely, as snakes may also be present there.
There are also simple methods that can help keep snakes away from the house.
