Smart Cleaning of Road Pavements
M. RAMA MANIKANTA1, CH. SRINIVAS2, K. HARI KRISHNA3, J.N.D. PANDU RANGA RAO4, P.V.R. ARUN KUMAR5, B. AKHIL6
1Assistant Professor, Department of Civil Engineering,Godavari Institute of Engineering & Technology(Autonomous), Rajahmundry.
2Head of the Department , Department of Civil Engineering,Godavari Institute of Engineering & Technology(Autonomous), Rajahmundry.
3,4,5,6 B.Tech Student, Department of Civil Engineering, Godavari Institute of Engineering & Technology(Autonomous), Rajahmundry.
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Abstract - With the growing demands of urbanization, traditional methods of road pavement cleaning often struggle to meet the efficiency, environmental, and cost-effectiveness requirements of modern cities. The concept of smart cleaning offers a promising solution by integrating advanced technologies like Internet of Things (IoT), artificial intelligence (AI), and autonomous systems to optimize street cleaning operations. Smart cleaning systems utilize IoT sensors placed on pavements and cleaning machines to collect real- time data on dirt levels, debris, and waste accumulation. This data is processed by AI algorithms to determine optimal cleaning schedules and routes, focusing on high-priority areas while reducing the need for unnecessary cleaning. These systems help to conserve resources, such as water and energy, by ensuring they are used efficiently. One of the key benefits of smart cleaning is environmental sustainability. Many systems are powered by electricity or solar energy, reducing reliance on fossil fuels. Additionally, smart cleaning machines often use waterless cleaning technologies or consume significantly less water compared to traditional methods. The use of biodegradable detergents further minimizes the environmental footprint.
Beyond sustainability, smart cleaning systems also offer improved operational efficiency and cost savings. Autonomous machines, such as robotic street sweepers, require minimal human intervention, reducing labour costs and improving the precision and consistency of cleaning. Furthermore, predictive maintenance capabilities ensure the longevity and optimal performance of equipment. Despite the clear advantages, challenges such as high initial investment, technology adaptation, and concerns about job displacement remain.
Key Words: Smart cleaning, Road pavements, Street sweeping, Sustainable cleaning, Internet of things(IoT), Artificial intelligence(AI), Urban maintenance, Data analytics, Smart sensors, Waste management, Resource optimization, Cost efficiency, Public health.
