Difference between revisions of "Desing and Implementation Of Long Lasting Key Finder With Bleetooth Low Energy"
(Created page with "400px|right|thumb ==Short Description== The rapid progress of wireless communications and embedded technologies has made wireless sensor and actuator ne...")
|Line 48:||Line 48:|
Latest revision as of 11:38, 21 July 2017
The rapid progress of wireless communications and embedded technologies has made wireless sensor and actuator networks (WSANs) possible. An emerging class of devices are the mobile and wearable wireless intelligent devices that can cover a wide range of application. The possible applications of wireless sensor network include smart living space, localization, environmental monitoring, smart building, etc. The main objective of this project is work in hardware and software to design a ultra low power wireless mobile device, eventually with sensors and GPS, that can be used as a key finder. The candidate will work with a micro-controllers, radio transceiver (for example CC2650 from Texas Instruments) and actuator (beeper) and sensors at firmware level to build up the network and the control algorithm. The hardware part can include also a redesign and optimization of the nodes' boards to build an ad-hoc solution with a small form factor and with only the needed components. The human interface application on Smartphone which is needed to interact with the mobile device and store the information can be part of the thesis according with the skills of the candidate students. Measurements of the system will be performed from the students in order to evaluate power consumption reduction, reliability, functionality and optimize the system. One of main goal of the design is to optimize the power consumption to allow the system to life several months without change the battery. THe project will be done in collaboration with Keyfinder.ch
- Looking for Semester and Master Project Students
- Supervisors: Michele Magno
- C Language
- Interest in Computer Architectures at system level
- PC or Smart-phone programming
- Knowledge of machine learning would be beneficial.
- Bluetooth Low energy is a plus.
- 30% Theory
- 50% Implementation
- 20% Testing