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Design, assembly, and deployment of MyVivarium RPi-IoT sensor system. a. Components of Pi-IoT sensor system include 1: Jumper wires (to extend reach) 2: SHT30 Temperature and humidity sensor with plastic shell casing 3: VL53L1X distance or time-of-flight sensor which can measure distance to a person (vivarium-worker) 4: VEML7700 illuminance sensor which can detect lights ON and OFF 5 and 6: STEMMA-QT connectors (for Raspberry Pi GPIO pins to sensors and between sensors) 7: Raspberry Pi 4B (2 GB) in a case with a cooling fan. b. Fritzing sketch of serial connections between I 2 C sensors and Raspberry Pi GPIO pins based on a validated sensor module build. Wire color designations are as follows – red: power (+ve), black: ground (-ve), yellow: SCL (serial clock), blue: SDA (serial data). Note that in a, the color of SDA (data) is white. c. Assembled sensor module deployed in our vivarium room. Sensors have been affixed to the lower part of the mouse cage transfer station. The Raspberry Pi has been placed in a corner of a mouse cage rack.

Journal: Computational and Structural Biotechnology Journal

Article Title: MyVivarium: A cloud-based lab animal colony management application with realtime ambient sensing

doi: 10.1016/j.csbj.2025.01.025

Figure Lengend Snippet: Design, assembly, and deployment of MyVivarium RPi-IoT sensor system. a. Components of Pi-IoT sensor system include 1: Jumper wires (to extend reach) 2: SHT30 Temperature and humidity sensor with plastic shell casing 3: VL53L1X distance or time-of-flight sensor which can measure distance to a person (vivarium-worker) 4: VEML7700 illuminance sensor which can detect lights ON and OFF 5 and 6: STEMMA-QT connectors (for Raspberry Pi GPIO pins to sensors and between sensors) 7: Raspberry Pi 4B (2 GB) in a case with a cooling fan. b. Fritzing sketch of serial connections between I 2 C sensors and Raspberry Pi GPIO pins based on a validated sensor module build. Wire color designations are as follows – red: power (+ve), black: ground (-ve), yellow: SCL (serial clock), blue: SDA (serial data). Note that in a, the color of SDA (data) is white. c. Assembled sensor module deployed in our vivarium room. Sensors have been affixed to the lower part of the mouse cage transfer station. The Raspberry Pi has been placed in a corner of a mouse cage rack.

Article Snippet: For each of our sensor modules, we used a Raspberry Pi model 4B with 2 GB RAM (Adafruit Industries LLC, NY) with a 128 GB RAM running the 64-bit Raspberry Pi Bookworm OS ( https://www.raspberrypi.com/software/ ).

Techniques:

Raspberry Pi 4B development board.

Journal: Sensors (Basel, Switzerland)

Article Title: Application of Traffic Cone Target Detection Algorithm Based on Improved YOLOv5

doi: 10.3390/s24227190

Figure Lengend Snippet: Raspberry Pi 4B development board.

Article Snippet: The number of frames transmitted per second during real-time detection by a network model is a key indicator of the selected model. As shown in , the embedded device used a Raspberry Pi 4B development board ( Manufactured by Raspberry Pi Foundation, bought from AN AVNET COMPANY, Shanghai, China),the configured 1.5 GHz quad-core CPU of which could run lightweight neural network models.

Techniques: