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An effective approach for solid waste management is essential for a myriad of different reasons presumed to protect the environment, leverage economic stability, and ensure sustainable development. Besides, with the rapid population expansion and urbanization, the waste generation is expected to further rise to 3.4 billion tons by 2050. This alarming increase in volume of trash demands proactive strategies for its appropriate management. However, in recent years, the waste management faced challenges to efficiently collect, sort, and compost complex waste. This incompetence has raised concerns regarding the current solid waste management practices. Thus, calling for modern technology and strategies to improve the waste management ecosystem. The integration of modern technologies, such as artificial intelligence (AI) to the existing practice can optimize waste handling processes. According to a study, waste management organizations adapting AI-based predictive maintenance experienced a 20% decrease in downtime, leading to seamless operations and lower maintenance costs. This consequently also helps improve economic stability and contribute toward energy recovery. Artificial intelligence (AI) has emerged as a potent solution that can automate the current waste management approaches. It works by optimizing the waste collection routes and enhancing sorting systems. Additionally, it can monitor large volumes of waste data to identify waste generation with up to 90% accuracy, and minimize the likelihood of improper disposal practices. Applying AI-driven techniques in the waste management ecosystem supports broader sustainability initiatives by increasing recycling rates and prolonging landfill life. Moving forward, as AI technologies evolve, it will become more capable of detailed analysis of waste streams and boost recycling rates via advanced analytics. The integration of IoT-enabled smart bins will facilitate real-time monitoring of waste levels, making operations process-efficient. Furthermore, AI will play a crucial role in energy recovery from waste materials, fostering economic stability while promoting a circular economy. Thus, leading to maximum resource recovery and minimum negative environmental impact.

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Synergizing AI, Energy Recovery, and Sustainability in Solid Waste Management

  • 章节

  • 发表日期：

    2026年

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  • Ankita Das,
  • Satya Ranjan Dash,
  • Shikta Singh

摘要

An effective approach for solid waste management is essential for a myriad of different reasons presumed to protect the environment, leverage economic stability, and ensure sustainable development. Besides, with the rapid population expansion and urbanization, the waste generation is expected to further rise to 3.4 billion tons by 2050. This alarming increase in volume of trash demands proactive strategies for its appropriate management. However, in recent years, the waste management faced challenges to efficiently collect, sort, and compost complex waste. This incompetence has raised concerns regarding the current solid waste management practices. Thus, calling for modern technology and strategies to improve the waste management ecosystem. The integration of modern technologies, such as artificial intelligence (AI) to the existing practice can optimize waste handling processes. According to a study, waste management organizations adapting AI-based predictive maintenance experienced a 20% decrease in downtime, leading to seamless operations and lower maintenance costs. This consequently also helps improve economic stability and contribute toward energy recovery. Artificial intelligence (AI) has emerged as a potent solution that can automate the current waste management approaches. It works by optimizing the waste collection routes and enhancing sorting systems. Additionally, it can monitor large volumes of waste data to identify waste generation with up to 90% accuracy, and minimize the likelihood of improper disposal practices. Applying AI-driven techniques in the waste management ecosystem supports broader sustainability initiatives by increasing recycling rates and prolonging landfill life. Moving forward, as AI technologies evolve, it will become more capable of detailed analysis of waste streams and boost recycling rates via advanced analytics. The integration of IoT-enabled smart bins will facilitate real-time monitoring of waste levels, making operations process-efficient. Furthermore, AI will play a crucial role in energy recovery from waste materials, fostering economic stability while promoting a circular economy. Thus, leading to maximum resource recovery and minimum negative environmental impact.