Promoting Sustainable and Innovative Waste Management in the 4th Industrial Revolution (4IR) Era
A special issue of Sustainability (ISSN 2071-1050). This special issue belongs to the section "Sustainable Management".
Deadline for manuscript submissions: closed (31 December 2022) | Viewed by 20459
Special Issue Editors
Interests: adsorption; advanced oxidation process; membrane filtration; photodegradation
Special Issues, Collections and Topics in MDPI journals
Interests: UAV; earth observation and forestry
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
Since 2015, the United Nations (UN) Member States have adopted a set of 17 Sustainable Development Goals (SDGs) that have become a reference agenda for addressing a variety of global challenges. Several goals like "decent work and economic growth" and "industry, innovation and infrastructure," refer to technology and collective efforts as a way of achieving "peace and prosperity for people and the planet, now and into the future."
The emergence of the 4th Industrial Revolution revolutionizes the way we address the solid waste problem by improving environmental protection using innovative solutions. In recent years, novel technologies such as artificial intelligence, machine learning, deep learning, and digitization have been developed as intelligence supports to transform the problem of solid waste management into zero-waste by applying a resource recovery paradigm towards a circular economy (CE). The applicability of different smart and sustainable technological solutions and how to achieve the 2030 UN Agenda are essential to promote the rapid development of sustainability. The benefits of such smart technologies should be based on the nexus of sustainability and cost-effectiveness to minimize potential harmful impacts to the environment and maximize benefits.
To complement the body of knowledge, this Special Issue welcomes a variety of contributions in the form of research work and/or review articles in the field of environmental protection. We welcome contributions that include solid waste management, water treatment, and air pollution control that particularly apply (but are not limited to) the following technologies: artificial intelligence, machine learning, deep learning, cloud computing, or digitization.
Dr. Tonni Agustiono Kurniawan
Dr. Ram Avtar
Dr. Deepak Singh
Guest Editors
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Keywords
- artificial intelligence
- deep learning
- digitization
- machine learning
- waste management
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