Environmental Monitoring and Assessment - Special Issue: Utilizing AI-Driven Systems for Industrial Waste Treatment
The current waste management systems are incapable of coping with the vast quantities of garbage produced every day. By moving to AI for smart industrial waste management, disposal procedures can be automated, resulting in more sustainable recycling ways. In our daily life, Artificial intelligence is rising in popularity in a wide range of applications in the field of waste treatment, which is considered a low energy process. The AI model could be incorporated with existing technology for industrial waste treatment for a sustainable environment. The employment of artificial intelligence (AI) and other intelligent methodologies in industrial waste systems has brought several advancements in environmental issues.
Continuous AI research is contributing to the emergence of new technical innovations and opportunities, with advantages of high requirements and an "eco-friendly" approach, which are the most common modern requests for any new technology. This AI-based strategy offers a hopeful, practical, methodology for upgrading and improving current industrial waste treatment. The smart industrial waste treatment system is an industrial automation system that is unique and productive. RFID tags and sensors are used to categorize the waste created and arrange it in different tags then identified by a pneumatic disposal device, a central system that stores all of this information, and calculates the best way to dispose of the overall waste generated. This system as a whole can also enhance its efficiency over time by analyzing the previous records. Waste processing robots have started to be used in garbage sites. Traditional waste sorting methods are slowly being replaced by automated intelligence equipment. The robots, who are proficient at multitasking, can sort tons of waste in a single day. Such large-scale systems have enormous potential for use in a variety of sectors. The Challenges faced in implementing AI-based smart system industrial waste are the availability of data, if the data is inconsistent, it will bring many problems while processing, integration with other technologies will create interoperability issues and the cost is much expensive. AI-based applications in industrial waste treatment yield better results, pushing processing steps to a whole new standard of performance and integrity. We can expect a massive decrease in the total waste generated worldwide if we seek a suitable way of disposing of industrial waste. This will go a long way toward conserving the environment for a healthier and better society. This Special Issue addresses the current need for smart systems based on artificial intelligence for industrial waste treatment.
AI-driven systems for industrial waste treatment provides a new paradigm to address the growing challenge of global energy and environmental challenges. The main objective of this study is to design an integrated multiagent system architecture for the management of industrial waste treatment and disposal. The need to explore AI-driven systems is a particular concern as waste treatment technologies become more sophisticated and complex. AI could be leveraged to optimize the mechanical and electrical components of advanced processes, driving increases in efficiency and effectiveness. In the past, the development of industrial waste treatment has been affected by the lack of effective waste processing techniques. As technology advances, so too does the need for better and more cost-effective treatment systems to be in place. AI-Driven Systems for Industrial Waste Treatment is one of the most sophisticated ways that waste treatment has advanced in recent years; this technology is growing more sophisticated by the day. AI-Driven Systems for Industrial Waste Treatment is one of the latest technologies to get rid of industrial waste. It efficiently controls the entire process of treatment of industrial waste and ensures high performance. Industrial waste treatment systems are often expensive and require a huge capital investment. They also involve dangerous chemicals that can cause death, serious injuries or pollution in the environment. In part due to these risks, current chemical-based industrial waste treatment methods don't often achieve high recycling accuracy and cannot attract young talent as they are completely manual processes with no AI-driven mechanization involved. AI-Driven Systems for Industrial Waste Treatment is an innovative and groundbreaking book, which focuses on the benefits of artificial intelligence and machine learning-driven systems for improving the quality of life, human health, and the environment. The implementation of AI-Driven Systems in waste treatment plants or other industrial processes allows for achieving significant improvements in efficiency, quality, and cost reduction. This also, intimates researchers and the scientific community to do further research practices in this field. This Special Issue will act as a key to motivating so many researchers working on the topic of Industrial waste treatment.
Timetable:
Manuscript submission: 30 November 2022
Guest Editors:
Dr. Chongqing Wang
Central South University, Zhengzhou University, China
Email: cqwang1990@zzu.edu.cn; cqwang2022@163.com
Dr. Mika Sillanpaa
Department of Biological and Chemical Engineering, Aarhus University, Norrebrogade 44, 8000 Aarhus C, Denmark
Email: mikasillanpaa@bce.au.dk; mikaesillanpaa@gmail.com
Prof. Vijay Kumar Thakur
Scotland’s Rural College, Biorefining and Advanced Materials Research Centre, Edinburgh, United Kingdom
Email: Vijay.Thakur@sruc.ac.uk; Vijay.Thakur@sruc.ac.uk