David Cuartielles, Malmo University / Arduino, Sweden

Adel Mellit, University of Jijel, Algeria

Marcelo Rovai, Federal University of Itajuba, Brazil

Rosdiadee Nordin, Sunway University, Malaysia

Marco Zennaro, ICTP, Italy

By moving computation closer to the data source, we can address critical barriers such as high latency, prohibitive bandwidth costs, and data privacy concerns. This collection seeks to highlight how Edge AI can empower marginalized communities, providing real-time insights in environments where traditional digital infrastructure is sparse or non-existent. We aim to bridge the gap between high-level algorithmic research and practical, field-ready deployments that drive social and economic impact.

Resource-Constrained Machine Learning: Techniques such as model pruning, quantization, and knowledge distillation for deployment on low-power microcontrollers.

Precision Agriculture: Edge-based crop disease detection, automated irrigation systems, and livestock monitoring in remote areas.

Global Health & Diagnostics: Real-time epidemic tracking, and wearable health monitors that function offline.

Environmental Monitoring: Decentralized systems for illegal logging detection, wildlife tracking, and localized air/water quality sensing.

Infrastructure & Energy: Smart grid management at the edge and decentralized waste management systems.

Ethics and Governance: Privacy-preserving on-device learning (e.g., Federated Learning) and addressing algorithmic bias in localized datasets.

Connectivity-Agnostic Solutions: Hybrid edge-cloud architectures designed specifically for intermittent or low-bandwidth environments.

Solar power systems: Edge AI applications for solar power systems, including real-time fault detection and diagnosis, predictive maintenance, smart monitoring using TinyML models, smartphone inspection and image analysis.

Review of abstracts: A rolling review process will begin during the final weeks of the call. This will allow early submissions to receive feedback promptly. All reviews will be completed within one month of the call’s closing. Selected authors will receive invitations to submit full manuscripts.

Manuscript development window: Authors will have until September 30th to submit manuscripts between 4,000 and 5,000 words. Manuscripts will then undergo peer review. Once authors receive their peer reviews, they will have a maximum of 2 weeks to send their final version. The special issue will be published in December 2026.

For more information, contact the editorial team at info@ircai.org.