Date of Award

12-2018

Document Type

Thesis

Degree Name

Master of Science (MS)

Department

Computer Engineering and Sciences

First Advisor

Josko Zec

Second Advisor

Carlos Otero

Third Advisor

Ming Zhang

Fourth Advisor

Philip Bernhad

Abstract

Internet of Things (IoT) brought a revolutionary change in embedded systems. It offloads the physical work of managing an equipment, appliance or device to a smart and network connected application. IoT makes it possible to monitor and control a huge network of devices remotely. The aim of this project is to develop a complete framework for smart data acquisition from a wireless sensor network to cloud servers. The framework includes configurable, low power, and small size embedded module that is attached to a sensor. The device reads data from the sensor and forwards them to the cloud server using the wireless interface. The server receives data from the device, configures devices, and creates a dashboard for user interactions. The device firmware can also be updated from the server without requiring any physical contact. The server software written for this framework is highly scalable, so it can be scaled on the cloud to handle many client devices at any location without requiring any changes in the code. As proof of concept, the data acquisition framework is implemented to constantly monitor radiation intensity. Continuous radiation monitoring can be useful in hospitals and research lab that uses radioactive materials to detect radiation leakage. Beta and Gamma radiation can penetrate living cells and cause cancer, skin burn or organ failure, so it is very critical that radiation is measured from a remote location. The amount of Beta and Gamma radiation is sensed using a Geiger-Muller tube and these data are collected by a very low power embedded device. The collected data is then sent to a server. The server set data retrieval intervals and device sleep cycles.

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