IoT and Artificial Intelligence for Sustainable Environments

Dear Colleagues,

Artificial Intelligence (AI) has emerged as a powerful enabler of sustainable development, offering novel solutions to address environmental, social, and economic challenges. At the same time, the sustainability of AI systems themselves, particularly their energy consumption and carbon footprint, has become an equally pressing concern. From this dual perspective, the integration of sensors and IoT infrastructures plays a central role: they provide the critical real-time data needed to monitor environmental conditions, assess resource efficiency, and optimize AI-driven decision making for sustainability.

Sensors and IoT devices enable the fine-grained monitoring of climate variables, urban infrastructures, agricultural ecosystems, and industrial processes. These data streams, when combined with advanced AI models and visualization techniques, can support predictive analytics, improve transparency, and foster informed decision-making at multiple scales. From tracking the carbon footprint of AI models to designing smarter circular economy strategies, the fusion of IoT-based sensing, AI analytics, and data visualization represents a cornerstone of next-generation sustainable solutions.

This Special Issue calls for contributions that explore the interplay of AI, data visualization, sustainability, and IoT-enabled data ecosystems, with a specific focus on how sensor data can be leveraged for impactful applications. We welcome submissions that present innovative techniques, frameworks, and real-world experiences, addressing both theoretical advances and applied case studies.

Dr. Giovanni Delnevo
Dr. Chiara Ceccarini
Guest Editors

Manuscript Submission Information

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Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.