STREET TREE HEALTH MONITORING

academic - group / 2021 / sensing installation prototype programs used: Arduino microcontroller, Illustrator

Improving street tree health often requires addressing systemic largescale problems and so it maybe futile to attempt to better a tree’s conditin on a tree-by-tree basis. Yet, public awareness is an important component of catalyzing systemic change and data collection is necessary to making a strong case. The Vitalitree Street Tree Health Monitor works towards this end. For the prototype, We used an Arduino microcontroller and a number of sensors to measure four of the seven common factors that impact tree health, including heat stress and PM 2.5 particle build up. The collected data was then aggregated into a weighted score, sent to a database via a LoRA network, and presented on the face of the monitor to describe the tree’s condition. I was responsible for assessing the tree’s foliage health. I used a near infrared sensor and applied the NDVI formula to assess weather the leaves are within a healthy range. I also created the monitor’s design and the project graphics.

To learn more about the project and see a video of the sensor in operation, click here. To follow a tutorial of how to use a near infrared sensor to determine foliage health, click here void loop() { sensor.takeMeasurements(); if (sensor.getVersion() == SENSORTYPE_AS7263) { NDVI_est = NDVI_eq(sensor.getCalibratedV(), sensor.getCalibratedS()); //run NDVI equation function with S (680 nm) & V (810 nm) wavelength readings if (( NDVI_est > 0.2) && (NDVI_est < 0.8)) { Serial.println(“HEALTHY”); digitalWrite(GREEN, HIGH); //turn on green LED } else { Serial.println(“UNHEALTHY”); digitalWrite(RED, HIGH); //turn on red LED } float NDVI_eq(float a, float b) { //create function for NDVI equation float result; result = (a-b)/(a+b); return result; } installation photos code excerpts