Project

# Title Team Members TA Documents Sponsor
73 Occupancy Counter
Aryan Mathur
Ashwin Provine
Tanmay Kant
Jialiang Zhang design_document1.pdf
final_paper1.docx
presentation1.pptx
proposal1.pdf
Team Members: Tanmay Kant (tkant2) Ashwin Provine (provine4) Aryan Mathur (aryanm6)

PROBLEM

In large building environments, managing energy consumption efficiently, particularly for heating, ventilation, and air conditioning (HVAC) systems, presents a significant challenge. HVAC systems often operate on a fixed schedule, with little regard for the actual occupancy of a space, leading to unnecessary energy use and increased operational costs. This inefficiency is especially pronounced in spaces like offices or small meeting rooms due to constant movement. The motivation for the occupancy counter project is to enable more intelligent and adaptive HVAC control by accurately tracking the number of people in a given space. Our experience in the ECE391 Lab (ECEB3026) was a perfect example of HVAC not recognizing the amount of students working late in the lab, with temperature fluctuating constantly. By aligning HVAC operations with real-time occupancy levels, this technology aims to significantly reduce energy consumption and operational costs for large buildings. Achieving precise occupancy counts allows for the HVAC system to adapt its output to the current need, ensuring that energy is not wasted heating, cooling, or ventilating spaces that are not in use or are only partially occupied. Additionally, this system supports a more sustainable approach to building management by reducing the carbon footprint associated with unnecessary energy use.

SOLUTION

Our project is an occupancy counter for rooms. It will utilize [a] Time of Flight Sensor Module(s) for the recognition of room occupants, where we will either use one module, splitting between two zones, or use two modules in order to determine whether the target is entering or exiting the room. The brains behind the sensor will be a WiFi-enabled Arduino Board that will decide the direction of the person’s transit, keeping track of how many people are present in the room. It will update a web interface that can be connected to by any user. The whole device will be powered by USB power brick(s).

SOLUTION COMPONENTS

Control Unit “The ESP8266 is a high-performance wireless SOC that offers maximum utility at the lowest cost and unlimited possibilities for embedding WiFi functionality into other systems.” This module will be the brain and mouth of our project, where data received will be broken down into a few key components, calculated, and sent out as a summary. The data will be analyzed to decide whether the target is moving from Zone 1 to Zone 2 or conversely. From there, the brain will add or subtract to the room count. Once this is complete, the data will be beamed via WiFi to a digital display (monitor, tablet, phone).

Sensor(s) “The VL53L1X is a state-of-the-art, Time-of-Flight (ToF), laser-ranging sensor, enhancing the ST FlightSense™ product family. It is the fastest miniature ToF sensor on the market with accurate ranging up to 4 m and fast ranging frequency up to 50 Hz.” This module acts as the eyes for our project, where the timing of a person crossing the tracked region will be acted upon using a state machine to see the current status.

For example: Entrance ----- Zone 1 ----- Zone 2 ----- Room Stat. A Stat. B Stat. C Stat. D When a person enters, their status will change from A, B, C, to D finally. Should they be exiting, their status will change from D, C, B, to A finally. If a person reaches a status of B or C, but does not continue their transit entering or exiting, respectively, we will not update the counter of the room since the occupancy has not changed.

Power This is the simplest part of the build, where we will use a USB-enabled power brick to provide power to the modules and connect it through a slim and long USB cable. The power for the VL53L1X will be between 2.8V to 5.5V, with the voltage properly regulated by the sensor carrier board while the power for the ESP8266 will be a standard 3.3V input, both powered by DC current.

CRITERION FOR SUCCESS

Exactness/error of count: the count must be exact for up to six occupants, and correct within plus/minus of one person for up to twelve. Since this project is being used as a dependency for a much bigger system, precision and accuracy are important. The actual display should update between two to ten times per minute. This is to ensure that our count is considered live and makes an impact on the energy-saving and HVAC procedures that will ensue. Output data will be transferred via a wireless (WiFi) connection to a display. The sensor we are using has a built-in web interface that can be enabled during setup which will allow for universal access for users of the project.

Low Cost Myoelectric Prosthetic Hand

Michael Fatina, Jonathan Pan-Doh, Edward Wu

Low Cost Myoelectric Prosthetic Hand

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According to the WHO, 80% of amputees are in developing nations, and less than 3% of that 80% have access to rehabilitative care. In a study by Heidi Witteveen, “the lack of sensory feedback was indicated as one of the major factors of prosthesis abandonment.” A low cost myoelectric prosthetic hand interfaced with a sensory substitution system returns functionality, increases the availability to amputees, and provides users with sensory feedback.

We will work with Aadeel Akhtar to develop a new iteration of his open source, low cost, myoelectric prosthetic hand. The current revision uses eight EMG channels, with sensors placed on the residual limb. A microcontroller communicates with an ADC, runs a classifier to determine the user’s type of grip, and controls motors in the hand achieving desired grips at predetermined velocities.

As requested by Aadeel, the socket and hand will operate independently using separate microcontrollers and interface with each other, providing modularity and customizability. The microcontroller in the socket will interface with the ADC and run the grip classifier, which will be expanded so finger velocities correspond to the amplitude of the user’s muscle activity. The hand microcontroller controls the motors and receives grip and velocity commands. Contact reflexes will be added via pressure sensors in fingertips, adjusting grip strength and velocity. The hand microcontroller will interface with existing sensory substitution systems using the pressure sensors. A PCB with a custom motor controller will fit inside the palm of the hand, and interface with the hand microcontroller.

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