Next-Generation Autonomous Biochemical Sensing: Materials, Algorithms, and Applications for Long-Term Reliability

Autonomous biochemical sensing is revolutionizing environmental monitoring, healthcare diagnostics, food safety, and smart agriculture by enabling rapid, on-site detection of molecular and ionic targets without direct human intervention. Building on insights from the latest WEF publication and the curations in Frontiers, this Research Topic aims to highlight and drive forward the multidisciplinary advances required to address persistent challenges in long-term autonomous operation.

Key areas of interest include:

- Advanced Anti-fouling Materials and Coatings: Innovations to overcome sensor surface degradation in real-world conditions.
- Next-Generation Recognition Elements: Development of robust and highly selective biorecognition components (e.g., aptamers, engineered proteins, synthetic receptors).
- Machine Learning and Autonomous Calibration: New computational approaches for drift correction, data validation, and multi-analyte detection with minimal manual oversight.
- Integration with IoT and Edge Devices: Hardware and software approaches to ensure data security, scalability, and utility in field-deployable scenarios.
- Emerging Applications: Showcasing breakthroughs in healthcare, environmental sensing, precision agriculture, and industrial monitoring enabled by autonomous biochemical sensor networks.

This Topic seeks contributions in original research, methods, perspectives, and reviews, particularly those that demonstrate translational potential and real-world deployment. By bringing together leaders from sensor technology, materials science, data science, and application domains, the aim is to foster collaboration and accelerate progress toward fully autonomous, reliable biochemical sensing systems.