Environmental Management: Smart Solutions

Environmental Management: Smart Solutions (JEMSS) is one of the spinoff-journals launched under the Journal of Environmental Management (JEM) series, dedicated to publishing cutting-edge research at the intersection of environmental science and digital innovation. As part of the JEM family, JEMSS benefits from the series’ strong reputation and global readership, providing a high-visibility platform for interdisciplinary studies.

JEMSS focuses on the transformative role of big data, artificial intelligence (AI), machine learning (ML), deep learning, generative AI, conventional simulation modeling and other computational technologies in solving complex environmental challenges. The journal aims to showcase how smart technologies and innovative approaches can enhance environmental monitoring, prediction, decision-making, and sustainable resource management across diverse ecosystems.

The journal encourages submissions that integrate advanced algorithms, modeling frameworks, and intelligent systems to address real-world problems in pollution control, climate resilience, ecological restoration, and environmental planning. It welcomes both fundamental research and applied studies, promoting scalable solutions that bridge theory and practice.

Topics of Interest Include (but are not limited to):

• AI-enhanced environmental monitoring

  using big data, IoT, citizen science and remote sensing

• Machine learning and deep learning models

  for environmental prediction, risk assessment, and decision support

• Generative AI and scene-based applications

  , such as image recognition, automated classification, and pattern detection in ecological data

• Digital twin technologies

  and simulation models for proactive environmental management

• Smart sensor networks

  , autonomous systems, and robotics in pollution control and ecosystem surveillance

• Optimization of resource use

  , energy efficiency, and waste management through data analytics

• Hybrid modeling approaches

  combining physical, statistical, and AI-based methods

• Smart city and urban sustainability solutions

  , including transportation, infrastructure, and climate adaptation

• Explainable AI (XAI)

  and ethical frameworks for transparent and responsible environmental decision-making

• Data integration and fusion

  across heterogeneous sources for comprehensive environmental analysis

• Actionable modeling and science

  that can lead to productive decision making through stakeholder engagement and innovative ways of influencing human behavior and management decisions.

JEMSS serves a broad audience of scientists, engineers, data scientists, and policymakers working toward sustainable environmental solutions. It supports interdisciplinary collaboration across environmental science, computer science, engineering, and social science domains.

The journal accepts a variety of article types, including:

• Full-length research articles

• Review articles

• Short communications

• Opinions and perspectives

Interested in organizing a Special Issue? We welcome proposals for special issues or virtual special issues within the scope of JEMSS. Please contact Prof. Peter Hooda and refer to the Journal of Environmental Management Guide for Authors for submission guidelines.