AI-Enhanced Decision Support Systems for Optimizing Hazardous Waste Handling in Civil Engineering
| International Journal of Civil Engineering |
| © 2023 by SSRG - IJCE Journal |
| Volume 10 Issue 11 |
| Year of Publication : 2023 |
| Authors : Vidhya Lakshmi Sivakumar, A.S. Vickram, Ragi Krishnan, Titus Richard |
10.14445/23488352/IJCE-V10I11P101
How to Cite?
Vidhya Lakshmi Sivakumar, A.S. Vickram, Ragi Krishnan, Titus Richard, "AI-Enhanced Decision Support Systems for Optimizing Hazardous Waste Handling in Civil Engineering," SSRG International Journal of Civil Engineering, vol. 10, no. 11, pp. 1-8, 2023. Crossref, https://doi.org/10.14445/23488352/IJCE-V10I11P101
Abstract:
The planning, monitoring, and mitigating hazardous waste in civil engineering projects is complex and vital to safeguard the environment and public health. Recently, AI has become a strong tool for optimizing dangerous waste treatment. This paper examines how AI is used in civil engineering Decision Support Systems to improve hazardous waste management’s efficiency, safety, and sustainability. Hazardous waste in civil engineering presents issues and requires innovative solutions. It then discusses how machine learning algorithms, data analytics, and predictive modelling optimize trash collection, transportation, treatment, and disposal. These AI-enhanced technologies improve risk assessment and environmental compliance by monitoring and making real-time decisions. This study examines case studies and projects of AI-based Decision Support Systems to determine their pros and cons. It covers AI’s ethical and regulatory implications in hazardous waste management. AI-enhanced Decision Support Systems may optimize hazardous waste handling in civil engineering, reducing environmental impact, improving safety, and increasing productivity. This research shows that AI might revolutionize dangerous waste management in civil engineering projects and encourage sustainable, environmentally friendly solutions.
Keywords:
Artificial Intelligence (AI), Decision Support Systems, Hazardous waste management, Civil engineering, Sustainability.
References:
[1] Khandoker Samaher Salem et al., “A Critical Review of Existing and Emerging Technologies and Systems to Optimize Solid Waste Management for Feedstocks and Energy Conversion,” Matter, vol. 6, no. 10, pp. 3348-3377, 2023.
[CrossRef] [Google Scholar] [Publisher Link]
[2] Jagadeesh Kumar Janga, Krishna R. Reddy, and K.V.N.S. Raviteja, “Integrating Artificial Intelligence, Machine Learning, and Deep Learning Approaches into Remediation of Contaminated Sites: A Review,” Chemosphere, vol. 345, 2023.
[CrossRef] [Google Scholar] [Publisher Link]
[3] Mohamed T. El-Saadony et al., “Hazardous Wastes and Management Strategies of Landfill Leachates: A Comprehensive Review,” Environmental Technology & Innovation, vol. 31, 2023.
[CrossRef] [Google Scholar] [Publisher Link]
[4] Nitasha Vig, Khaiwal Ravindra, and Suman Mor, “Environmental Impacts of Indian Coal Thermal Power Plants and Associated Human Health Risk to the Nearby Residential Communities: A Potential Review,” Chemosphere, vol. 341, 2023.
[CrossRef] [Google Scholar] [Publisher Link]
[5] Mashura Shammi et al., “Application of Short and Rapid Strategic Environmental Assessment (SEA) for Biomedical Waste Management in Bangladesh,” Case Studies in Chemical and Environmental Engineering, vol. 5, 2022.
[CrossRef] [Google Scholar] [Publisher Link]
[6] Elham Eslami et al., “Enhancing Resource Efficiency and Sustainability in Tomato Processing: A Comprehensive Review,” Journal of Cleaner Production, vol. 425, 2023.
[CrossRef] [Google Scholar] [Publisher Link]
[7] Hamed Nabizadeh Rafsanjani, Amir Hossein Nabizadeh, “Towards Human-Centered Artificial Intelligence (AI) in Architecture, Engineering, and Construction (AEC) Industry,” Computers in Human Behavior Reports, vol. 11, 2023.
[CrossRef] [Google Scholar] [Publisher Link]
[8] Katarzyna Borys et al., “Explainable AI in Medical Imaging: An Overview for Clinical Practitioners – Beyond Saliency-Based XAI Approaches,” European Journal of Radiology, vol. 162, 2023.
[CrossRef] [Google Scholar] [Publisher Link]
[9] Hong Hao et al., “Towards Next Generation Design of Sustainable, Durable, Multi-Hazard Resistant, Resilient, and Smart Civil Engineering Structures,” Engineering Structures, vol. 277, 2023.
[CrossRef] [Google Scholar] [Publisher Link]
[10] Shaili Vyas et al., “Solid Waste Management Techniques Powered by In-Silico Approaches with a Special Focus on Municipal Solid Waste Management: Research Trends and Challenges,” Science of the Total Environment, vol. 891, 2023.
[CrossRef] [Google Scholar] [Publisher Link]
[11] Pascual Ferrans et al., “Sustainable Urban Drainage System (SUDS) Modeling Supporting Decision-Making: A Systematic Quantitative Review,” Science of the Total Environment, vol. 806, 2022.
[CrossRef] [Google Scholar] [Publisher Link]
[12] Gopaiah Talari et al., “State of the Art Review of Big Data and Web-Based Decision Support Systems (DSS) for Food Safety Risk Assessment with Respect to Climate Change,” Trends in Food Science & Technology, vol. 126, pp. 192-204, 2022.
[CrossRef] [Google Scholar] [Publisher Link]
[13] Simon Elias Bibri et al., “Smarter Eco-Cities and Their Leading-Edge Artificial Intelligence of Things Solutions for Environmental Sustainability: A Comprehensive Systematic Review,” Environmental Science and Ecotechnology, vol. 19, 2023.
[CrossRef] [Google Scholar] [Publisher Link]
[14] Gerald K. Ijemaru, Li Minn Ang, and Kah Phooi Seng, “Transformation from IoT to IoV for Waste Management in Smart Cities,” Journal of Network and Computer Applications, vol. 204, 2022.
[CrossRef] [Google Scholar] [Publisher Link]
[15] Shiv Bolan et al., “Review on Distribution, Fate, and Management of Potentially Toxic Elements in Incinerated Medical Wastes,” Environmental Pollution, vol. 321, 2023.
[CrossRef] [Google Scholar] [Publisher Link]
[16] Joshua C. Morganstein, “Preparing for the Next Pandemic to Protect Public Mental Health: What Have We Learned from COVID-19?,” Psychiatric Clinics of North America, vol. 45, pp. 191-210, 2022.
[CrossRef] [Google Scholar] [Publisher Link]
[17] M.A. Hannan et al., “Solid Waste Collection Optimization Objectives, Constraints, Modeling Approaches, and Their Challenges toward Achieving Sustainable Development Goals,” Journal of Cleaner Production, vol. 277, 2020.
[CrossRef] [Google Scholar] [Publisher Link]
[18] Saydul Akbar Murad et al., “A Review on Job Scheduling Technique in Cloud Computing and Priority Rule Based Intelligent Framework,” Journal of King Saud University - Computer and Information Sciences, vol. 34, pp. 2309-2331, 2022.
[CrossRef] [Google Scholar] [Publisher Link]
[19] Rajendiran Naveenkumar et al., “A Strategic Review on Sustainable Approaches in Municipal Solid Waste Management and Energy Recovery: Role of Artificial Intelligence, Economic Stability and Life Cycle Assessment,” Bioresource Technology, vol. 379, 2023.
[CrossRef] [Google Scholar] [Publisher Link]
[20] Rachel Krebs et al., “Biotechnology to Reduce Logistics Burden and Promote Environmental Stewardship for Air Force Civil Engineering Requirements,” Biotechnology Advances, vol. 69, 2023.
[CrossRef] [Google Scholar] [Publisher Link]
[21] Dhinesh Kumar R., and Rammohan A., “Revolutionizing Intelligent Transportation Systems with Cellular Vehicle-to-Everything (C-V2X) Technology: Current Trends, Use Cases, Emerging Technologies, Standardization Bodies, Industry Analytics and Future Directions,” Vehicular Communications, vol. 43, 2023.
[CrossRef] [Google Scholar] [Publisher Link]
[22] Jianqi Zhang et al., “Automated Guided Vehicles and Autonomous Mobile Robots for Recognition and Tracking in Civil Engineering,” Automation in Construction, vol. 146, 2023.
[CrossRef] [Google Scholar] [Publisher Link]
[23] Yiqi Liu et al., “Transforming Data into Actionable Knowledge for Fault Detection, Diagnosis and Prognosis in Urban Wastewater Systems with AI Techniques: A Mini-Review,” Process Safety and Environmental Protection, vol. 172, pp. 501-512, 2023.
[CrossRef] [Google Scholar] [Publisher Link]
[24] Diego Gabriel Rossit, and Sergio Nesmachnow, “Waste Bins Location Problem: A Review of Recent Advances in the Storage Stage of the Municipal Solid Waste Reverse Logistic Chain,” Journal of Cleaner Production, vol. 342, 2022.
[CrossRef] [Google Scholar] [Publisher Link]
[25] Gaolei Wei et al., “Direct Recycling of Spent Li-ion Batteries: Challenges and Opportunities toward Practical Applications,” Iscience, vol. 26, no. 9, pp. 1-12 2023.
[CrossRef] [Google Scholar] [Publisher Link]
[26] Arpan Kumar Kar, Shweta Kumari Choudhary, and Vinay Kumar Singh, “How can Artificial Intelligence Impact Sustainability: A Systematic Literature Review,” Journal of Cleaner Production, vol. 376, 2022.
[CrossRef] [Google Scholar] [Publisher Link]
[27] Aniko Konya, and Peyman Nematzadeh, “Recent Applications of AI to Environmental Disciplines: A Review,” Science of the Total Environment, vol. 906, 2024.
[CrossRef] [Google Scholar] [Publisher Link]
[28] Yu Xie et al., “How does Environmental Regulation Affect Productivity? The Role of Corporate Compliance Strategies,” Economic Modelling, vol. 126, 2023.
[CrossRef] [Google Scholar] [Publisher Link]
[29] José Ramón Saura, Domingo Ribeiro-Soriano, and Daniel Palacios-Marqués, “Setting Privacy “by Default” in Social IoT: Theorizing the Challenges and Directions in Big Data Research,” Big Data Research, vol. 25, 2021.
[CrossRef] [Google Scholar] [Publisher Link]
[30] David B. Olawade et al., “Trends of Solid Waste Generation during COVID-19 Pandemic: A Review,” Waste Management Bulletin, vol. 1, no. 4, pp. 93-103, 2023.
[CrossRef] [Google Scholar] [Publisher Link]