Waste control and management are important aspects of maintaining cleanliness and environmental sustainability. In the rapid urbanization and industrialization era, waste production has increased significantly. Good waste management not only aims to reduce the volume of waste but also to optimize the reuse of materials that are still valuable and reduce negative impacts on public health and ecosystems. With a planned approach, waste management can be one of the keys to creating a cleaner, healthier, and more sustainable environment.
Azyze et al. (2022) and Tarmizi et al. (2022) developed an Internet of Things (IoT)-based waste monitoring system integrated with Telegram offering a modern solution for waste management, improving communication and efficiency in urban environments. The system uses sensors to monitor the filling level of bins in real time and sends this data to a central server. Integration with Telegram allows users, both waste management officers and residents, to receive notifications when bins are nearing capacity, facilitating timely collection and reducing overflows. The collected data can also be analyzed to optimize waste collection routes and schedules, thus improving operational efficiency. The system also improves communication about waste management activities, has a positive impact on the urban environment by reducing unnecessary trips by waste collection vehicles, and encourages community involvement to maintain cleanliness. This innovative approach streamlines the waste management process and promotes a cleaner and more sustainable urban living environment.
On the other hand, Bobulski and Kubanek (2022) made a plastic waste recognition robot as an innovative solution to improve waste management by automating the identification and sorting of plastic waste. Using advanced machine learning techniques, particularly convolutional neural networks (CNN), the robot can classify different types of plastic accurately. Key features include automated sorting, which improves recycling efforts and reduces contamination in the recycling stream, as well as the use of convolutional artificial neural networks that enable precise identification of different plastic materials. The robot is also designed for low cost but still high accuracy in identifying plastic bottles and other recyclable materials. Benefits include increased recycling rates, efficiency in waste management, and a positive environmental impact. This solution is a significant advancement in the handling of plastic waste.
By: I. Busthomi