Pratikkumar Desai

Semantic Gateway as a Service Architecture for IoT Interoperability

The Internet of Things (IoT) is set to occupy a substantial component of future Internet. The IoT connects sensors and devices that record physical observations to applications and services of the Internet[1]. As a successor to technologies such as RFID and Wireless Sensor Networks (WSN), the IoT has stumbled into vertical silos of proprietary systems, providing little or no interoperability with similar systems. As the IoT represents future state of the Internet, an intelligent and scalable architecture is required to provide connectivity between these silos, enabling discovery of physical sensors and interpretation of messages between the things. This paper proposes a gateway and Semantic Web enabled IoT architecture to provide interoperability between systems, which utilizes established communication and data standards. The Semantic Gateway as Service (SGS) allows translation between messaging protocols such as XMPP, CoAP and MQTT via a multi-protocol proxy architecture. Utilization of broadly accepted specifications such as W3Cs Semantic Sensor Network (SSN) ontology for semantic annotations of sensor data provide semantic interoperability between messages and support semantic reasoning to obtain higher-level actionable knowledge from low-level sensor data.

Indoor localization and surveillance usingwireless sensor network and Pan/Tilt camera

A system-level approach for indoor surveillance of objects using wireless sensor networks and Pan/Tilt camera is presented in this paper. The objects to be tracked carry a listener cricket mote and beacon motes are mounted on the ceiling. The Time Difference of Arrival (TDoA) approach and multilateration are used to estimate the distance and position of the object, respectively. The small error in the position estimation result was further reduced by implementing a Kalman filter. The position of the object obtained from the cricket motes are used to calculate the pan and tilt angles of the camera, also mounted on the ceiling. Since the camera used does not have the zoom capability, a laser pointer is used to constantly point a dot on the moving object. The pointer followed the object with negligible error.

System Level Approach for Surveillance Using Wireless Sensor Networks and PTZ Camera

A system-level approach for indoor surveillance of objects using cricket motes and PTZ cameras is presented in this paper. The objects to be tracked carry a listener mote with beacon motes mounted on the ceiling. The positions and orientation of the object received from the Cricket motes are used to calculate the pan, tilt and zoom of the camera which constantly track the moving object. The extended Kalman filter based approach is used to estimate the position of the objects in the absence of line of sight communication of the motes for limited amount of time.

INS aided by an acoustic wireless sensor network and magnetometer

The objective of this paper is to develop the theory for integrating magnetometer measurements with an existing inertial navigation system (INS) aided by an acoustic wireless sensor network. The system without magnetometer measurements provides position information reliably. However, in the absence of dynamic motion the orientation errors are not observable using the sensor network, which only provides position information. The magnetometer provides consistent observability of the orientation. The measurement model needed to estimate the orientation errors using the magnetometer is derived in this paper. This measurement model is integrated with measurements from the acoustic sensor network into a complimentary Kalman filter that is used to estimate the error states of an INS.

Indoor localization for global information service using acoustic wireless sensor network

Indoor localization with sensing capabilities is the missing link for a Geospatial Information System and sensor web. The sensor network is capable of environmental monitoring and geo-tagging sensor data. This paper presents a unique algorithm which uses fusion of Radio Signal Strength Indicator and Time Difference of Arrival for centimeter level accurate indoor localization using wireless sensor network motes. The paper also proposes the integration of various environmental sensors with wireless sensor network. The acquired sensor data can be geo-tagged with the translated global coordinates and additional sensory metadata. With the use of semantic sensor web, this sensor information can be utilized in various decision making scenarios for critical situations. The main goal of the paper is to use indoor localization assisted by sensor fusion and semantic web for first responders in emergency scenarios.