The rapid expansion of the Internet of Medical Things (IoMT) has enhanced healthcare services, but it has also exposed these systems to a growing range of cyberattacks. Addressing this challenge requires effective intrusion detection solutions. Machine learning-based intrusion detection systems (IDSs) offer a promising approach. In this research, we leverage IoMT-TrafficData, a recently published dataset specific to IoMT environments, to develop intrusion detection models based on federated learning (FL), which preserves data privacy while enabling the use of lightweight learning algorithms suited to resource-constrained devices. In addition, SHAP-based interpretability methods are employed to explain model decisions, thereby improving reliability and transparency. Compared with existing IDS solutions for IoMT, this research proposes an approach that balances performance, privacy, and interpretability while accounting for resource limitations, resulting in three unified, lightweight, and interpretable detection models tailored to different data types in IoMT environments. This work thus provides a solid foundation for future research on secure medical IoT systems.

Ituran's new traffic-monitoring contract with Israeli transport entities spans up to four years, with only the first year guaranteed.

The board approved entering a service agreement with Urban SDK to obtain near real-time traffic metrics (speed, volume, turning movements) using GPS/cell data; staff said the platform will accelerate traffic study turnaround and provide data to inform engineering solutions.

The pilot shares Cloudflare content-freshness and traffic data with OpenAI to test faster web indexing. No pricing or timeline was disclosed for wider rollout.

The pilot shares Cloudflare content-freshness and traffic data with OpenAI to test faster web indexing. No pricing or timeline was disclosed for wider rollout.

WUHU, China, Jan. 19, 2026 /PRNewswire/ — In December 2025, global traffic data analytics company INRIX released its 2025 Global Traffic Scorecard, providing an in-depth analysis of traffic data from over 900 cities across 36 countries. The report shows that traffic congestion has worsened in more than half of these cities compared to the previous year, making it a persistent challenge for major urban areas. Building on these insights, the LEPAS flagship model LEPAS L8 leverages advanced intelligent technologies and robust hybrid systems to deliver an Elegant Driving solution. Even in congested conditions, it reduces driver stress and allows them […]

Traffic-influenced routing is now available in public preview, bringing live and historical traffic data to standard routing, optimized routing, map matching, isochrones, and time/distance matrices.

AI-powered, privacy-friendly traffic counters for pedestrians, cyclists, cars, and heavy vehicles — available in both indoor and outdoor models. Includes an intuitive dashboard and an open API for eas...

🙋‍♂️ Community-powered data wins again! After nearly three decades of accidents, near-misses and calls for action, residents of London, Ontario's Old South neighbourhood in Canada finally got their f...