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NSF NeTs Bulldog Mote Project

Goals

The NSF NeTs Bulldog Mote Project project will focus on designing a new low power sensor node, Bulldog Mote, using various attractive low power techniques, such as energy harvesting, clock scheduling, dynamic voltage scheduling and low power design methods at all of WSNs multiple layers.

The subsequent comprehensive lower power design model for embedded devices will be studied and presented. Designers can evaluate and create their designs of embedded devices under tight power constrains using the procedure and methods presented in the low power design model. 

This project addresses the design and implementation of the following components:

  1. Efficient low-power methodologies implemented throughout all WSNs' design layers from the application to the physical layer
  2. A new WSN sensor node, the Bulldog Mote, created using various low power methodologies
  3. Energy harvesting technologies for sensor node architecture.

A low power design model will be created to design such embedded devices and made available to educators, students and engineers working in related areas. Furthermore, this research will provide the knowledge necessary to design enhanced sensor nodes for WSNs in terms of power consumption and communication ability. The same low-power design techniques can be used for a variety of other power constrained applications, such as consumer electronics and medical devices.

Project Progress 10/01/2020-09/30/2021

  • The final version of the low power Bulldog Mote PCB has been made. Design of the mote system has been done. Simulation of WSN operation using the motes is carrying out.  
  • Efficient low-power methodologies implemented throughout all WSNs' design layers from the application to the physical layer; 
  • Low power WSN communication protocols have been developed and simulated. New RDC/LS-AODV low power design method was simulated and results are satisfied.
  • Energy harvesting technologies for sensor node architecture. Several energy harvesting technologies were studied and simulated.  Solar and Wind based energy harvesting system are under testing for simulation and preliminary experiment results are being analyzed with 2nd PCB. Vibration, thermal and other energy harvesting technologies are being investigating for a possible addition of the energy sources.
  • Energy harvesting control architecture are being investigated for nonlinear control techniques such as fuzzy, sliding mode, neural network and so on.  Also with additional energy storages using battery and ultra-capacitor, a control architecture is being tested using simulation study.  

Project Progress 10/01/2019-09/30/2020

  • Low power WSN Design Methodologies
    • Efficient low-power methodologies implemented throughout all WSNs' design layers from the application to the physical layer; Low power WSN communication protocols have been developed and simulated. New RDC low power design method was simulated and results are satisfied.
  • A new WSN sensor node, the Bulldog Mote, created using various low power methodologies.
    • The first version of the newly designed low power Bulldog Mote PCB has been made and is under testing.
  • Energy harvesting technologies for sensor node architecture.
    • Several energy harvesting technologies were studied and simulated.  Solar and Wind based energy harvesting system are under testing for simulation and preliminary experiment results are being analyzed with 2nd PCB. Vibration, thermal and other energy harvesting technologies are being investigating for a possible addition of the energy sources.
  • Energy harvesting control architectures
    • Energy harvesting control architecturesare being investigated for  nonlinear control techniques such as fuzzy, sliding mode, neural network and so on.  Also with additional energy storages using battery and ultra capacitor, a control architecture is being tested using simulation study. 

Project Progress 10/01/2018-09/30/2019

  • Simulation of WSN communication protocols design and simulation, leading to publications of two IEEE conference papers.
  • Sensor sampling and processing design.
  • Wireless sensor communication and connection experiments.
  • WSN gateway and protocol design on physical network.

Last updated on 10/06/2021