Abstract
Waste has a direct impact on human health and the surrounding environment. Apart from the health aspect, many industries' growth is effected by waste material such as the food industry. Waste management authorities are interested in reducing the cost of waste management operations and searching for sustainable waste management solutions. For effective planning of waste management, reliable data analysis is required to produce results that can facilitate the planning process. Data mining and machine learning-based data analysis over the waste data can produce a more detailed, and in-time waste information generation, which can lead to effectively manage the waste amount of specific area. In this paper, a descriptive data analysis approach, along with predictive analysis, is used to produce in-time waste information. The performance of the proposed approach is evaluated using a real waste dataset of Jeju Island, South Korea. Waste bins are virtualized on its actual location on the Jeju map in Quantum Geographic Information Systems(QGIS) software. The performance results of the predictive analysis models are evaluated in terms of Mean Absolute Error(MAE), Root Mean Square Error (RMSE), and Mean Absolute Percentage Error(MAPE). Performance results indicate that predictive analysis models are reliable for the effective planning and optimization of waste management operations.
Highlights
Waste management is a collective name for all the processes carried out in the waste collection such as waste collecting, waste monitoring, and waste disposal, and recycling of waste
2) ROOT MEAN SQUARED ERROR(RMSE) Root Mean Square Error (RMSE) is one of the standard method to measure the error of a prediction model in quantitative data such as waste amount.RMSE can be understood as a type of distance between the vector of predicted waste amount and the vector of original waste amount
A descriptive data analysis approach, along with predictive analysis, is used to produce in-time waste information utilized by waste management authorities for the effective planning of waste management
Summary
Waste management is a collective name for all the processes carried out in the waste collection such as waste collecting, waste monitoring, and waste disposal, and recycling of waste. One aspect of effectively planning waste management operations is to reduce the cost. Authorities are interested in sustainable solutions for waste management to reduce the harmful effects of wastes on the health of humans, animals, and the environment Another aspect of effectively planning waste management is to reduce the generation of the waste amount and use fewer resources in the transportation, disposing of, and recycling of wastes. Monitoring of reliable spatial and timely accurate waste data along intelligent data-driven insights will be helpful in the planning of waste management operations. Imran et al.: Quantum GIS Based Descriptive and Predictive Data Analysis for Effective Planning of Waste Management bins than the other areas. We are utilizing the mapping capability of QGIS along with predictive analysis methods, to create useful in-time information for waste management authorities.
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