دانلود رایگان مقاله انگلیسی پشتیبانی تصمیم برای بهینه سازی مدیریت زباله - تیلور و فرانسیس 2018

ABSTRACT

During the last few decades, research into sustainability aspects of ICT grew rapidly for most organisational and business processes. Evolution towards the development of infrastructure for Smart Cities, Green ICT with application of decision support systems (DSSs) created opportunities for solving complex problems, for example, sensorenabled smart waste management. This paper focuses on supporting decisions for sustainable garbage collection route planning and optimisation. The objective is to create a practical solution for reducing CO2 emissions and reduce negative impact on the environment as a result. From the design science perspective, a DSS is proposed, researched and developed to increase the effectiveness of municipal waste management. The paper also evaluates this approach against the Green IS framework.

6. Conclusions and future work

The research presented in this paper focuses on the usage of DSS for Sustainable Development. Gholami et al. (2016) highlighted the lack of practical ‘impact-oriented’ solutions for the ill-structured questions of Green ICT and Sustainability, and the current project aims to fulfil this gap. As the example use case, the smart waste management case was chosen. The idea of the project was to create a decision support tool for the coordinators that allows the drivers of the garbage trucks to choose the optimal path for collecting garbage. It was also shown with the help of different scenarios that the modern way of garbage collection requires new and innovative solutions, and modifications to the garbage truck was suggested to improve the garbage collection process. By introducing such modifications, we have received more than a 50% reduction in both distance covered and CO2 emission.

The project has a potential for further research. First, the impact of the city size is an opportunity for future investigation. Secondly, the data collected from sensors and then processed by the DSS, can be used by the municipality for the prediction of the garbage bins fill trends. It is obvious that, for example, during the weekend garbage to a higher extent is generated in residential neighbourhoods than on weekdays, and, therefore, they might require their garbage bin to be emptied sooner. At the same time, there’s an opportunity to use the data from DSS as the foundation one for deciding where to build an incinerator and of which type. For example, offices in the city centre usually don’t produce much bio waste, whereas the amount of paper and plastic waste may be significant. It might be reasonable to have the incinerator for plastic and paper somewhere not far from the office part of the city, to reduce the distance HCTs would need to cover to bring the garbage to the incinerator.