David Tavilla

About Me: I am an ISSN (Information Support Services and Networking) instructor at Worcester Technical High School in Worcester, MA. I teach courses that prepare students for entry level careers in information technology, as well as future college level study in the field. I prepare students for industry standard certifications in IT, such as the CompTIA A+ Computer Repair Technician, Microsoft Azure Fundamentals, Cisco CCST, and VMWare Associate.

About the Lab: We are interested in understanding and enhancing the intelligence, usability and processing capabilities of tiny computing devices to realize their full potential in our daily lives. Our works will provide sustainable and scalable sensing solutions in various application domains ranging from health care to smart agriculture.

Project: Benchmark for Assessing Battery-Free Computing Systems

Weekly Updates:

  • Week 1: I started learning about battery-free systems and energy harvesting by reading research papers written by various groups working in the field of energy harvesting. Then, my research partner and I downloaded and characterized several datasets from diverse sources, including solar, kinetic, and RF energy gathering testbeds.
  • Week 2: This week we began working with the first energy dataset. The dataset contains solar energy data in volts from a sensor placed on the roof of a lab in Spain over the course of 2 months. Our goal is to characterize the dataset by how many anomalies it has, the predictability of data, and biases for time of day. We created a plot of the data and ran algorithms to count how many anomalies are in the data and give a mean squared error score for the dataset.
  • Week 3: During week three we researched the hardware we will need into order to build our testbed. We looked at several solutions for RF transmitters, reviewed the specifications and outputs of each device, and decided on our final selection. We also reviewed the other components we will need, including Arduinos and data loggers.
  • Week 4: This week we conducted a subjective analysis on the thermal data by comparing and contrasting dataset characteristics. I also obtained the Digilent Analog Discovery 2 USB oscilloscope, installed the Digilent Waveforms software, and took sample data in order to learn how to operate the device. We will use this later to analyze RF energy harvested from our testbed.
  • Week 5:

Poster and Lesson Plan:

(Link RET Lesson Plan Handout)

(Link RET Poster)