Traffic congestion detection is crucial for road traffic condition monitoring and improving traffic operation efficiency. In the field of transportation where vehicles are becoming more and more common, metropolitan areas are experiencing an increase in traffic congestion. Traffic flow monitoring technology is one of the most essential systems in intelligent transportation. Currently, traffic density estimation mostly relies either on traditional sensor-based infrastructure such as loop detectors and GNSS, which are economically expensive and maintenance-intensive, or more advanced computer vision-based methods such as CNN-based object counting. However, these traditional vision-based methods are not effective in dealing with variations in surveillance videos and only capture spatial features. This prompts us to explore density map-guided temporal transformers for traffic density estimation. This study proposes a deep learning framework that jointly models the spatial distribution of vehicles and their motion patterns across consecutive video frames, enabling more accurate monitoring of traffic conditions. The proposed system estimates the traffic density under different conditions and different road layouts. This approach offers a scalable solution for smart city traffic management and congestion reduction.

Health Information Technology (HIT) along with the Internet of Medical Things (IoMT) employs wearable technology to monitor diseases through its capability to prevent medical mistakes from occurring. The devices track vital signs which medical professionals use for precise treatment decisions through real-time data transmission. IoT-driven medical devices improve telehealth service delivery as well as enhance patient monitoring functions. Virtual and augmented reality powers educational wearables to assist medical student surgical training as well as human anatomy education. Research professionals obtain immediate biological feedback through their diagnostic work and clinical preparation. Wearable technology enhances healthcare operations through its support of educational initiatives and research activities which lead to better medical discoveries today and in upcoming years.