Multi-protocol IOT Gateway

Smart Sensing

Smart Sensing

Data Aggregation in Bluetooth Low Energy Networks

1- Abstract

Bluetooth Low Energy (BLE) technology exists in most of the up-to-date electronic devices such as mobile phone, tablets, and computers. The presence of such amount of devices triggers the possibility of integrating it into larger networks serving different purposes. Moreover, the mass production makes it possible to manufacture sensors with BLE enabled while the cost is still minimized. In this project, we are looking for a broad utilization of data collected from different types of sensors with enabled BLE, the data collected from these sensors will be integrated with the co-existing BLE chips in any electronic device will be aggregated to serve some objective such as anomaly detection, localization, and alerting services, etc.

2- Project Objective

The main objective of this project is developing a tool that utilizes the data collected from different anchors equipped with a Bluetooth low energy technology. This data will be aggregated and processed on the clouds for different purposes. For instance, it can be used for indoor navigation, anomaly detection, localization, and alerting services The project includes different development phases starting from the setup of sensors with BLE enabled, server installation, design, and implementation of suitable machine learning algorithms, the development of visualization tools, etc.

3- Milestones

  •      Development of web and mobile application for data aggregation and visualization.
  •      Developing an indoor localization, navigation, and anomaly detection algorithms.
  •      Design and implementation of machine learning algorithms for big data analysis.

4- Key Resources Required

  •      Machine Learning developers.
  •      Web application developers.
  •      Android mobile application developers.
  •      Embedded system developers excellent at C programming, HW interfacing.
  •      Very good knowledge of Linux.

5- Selection Criteria

  • Qualified candidates have to show their skills set and how it fits the requirements and the activities designated for this project.
  • It is highly recommended for students majoring in Computer Engineering, Computer Science, and Communications Engineering graduating in 2019.