"Ubiquitous Multi-Context Modeling (UMM) for Crowd Disaster Mitigation"

The proposed context aware framework UMM introduces a new module "Context Categorizer" in the existing frameworks to bring in non-redundancy and sharing of information to span multiple applications such as health-care, surveillance, agriculture sector etc. The single context information acquired is utilized for multiple applications. The objective of Master thesis is to bring in wireless sensor network for effective crowd monitoring which is a key requirement now-a-days due to alarming increase in death rates due to crowd disasters. The master thesis work deals with the implementation of UMM model for Crowd disaster mitigation by utilizing the potentials of sensing capabilities of Smart phones. The crowd disaster mitigation system makes use of embedded accelerometer, gyroscope, camera, microphone etc. of smart phone to predict the occurrence of stampede in a crowd based on distributed consensus by the participant nodes.

Team Members Leader Of the Team Faculty Student

Maneesha V. Ramesh

Rekha P.

Anjitha S.

RESEARCH AREAS Landslide Monitoring Healthcare Applications Water Quality Monitoring Remote Triggered Lab Underground Sensor Network Wireless Smart Grid Wireless surveillance Power Optimization Issues Heterogenous Wireless Networks and Network mobility Real-time video steaming and QoS Crowd Disaster Monitoring and Mitigation Wireless Robotics Participatory Sensing Mobile Adhoc Network Avoiding Water Vessel Collisions Wireless Power Transfer to Underground Sensors Multi-UAV Sensor Network Parametric Analysis Solar Thermal Energy System Solar Thermal Cooking System