In these tough times, where the danger of community spread of the deadly virus haunts every city, public health officers are faced with the dilemma of tracing from where a particular patient contracted the virus or to whom he/she transferred it to. Many patients intentionally hide details and many are not able to recollect the people they met or places they went to. Also, while going to public places it is not always possible to maintain the required distance.
To solve the mentioned problems there are very limited number of devices deployed, mostly by private agencies but nothing at the personal level. I wish to make a module that can be mounted on a cap that warns the wearer if a person comes too close. The module would also track the GPS location and click pictures of the persons the wearer has come in close proximity(less than 2m) to. The collected data would help trace down all possible people in danger if the wearer is found Covid-positive and timely quarantined.
I plan to make a smart cap with the PSoC 6 Pioneer kit as the main controller, fitted with a GPS module, TOF Proximity sensor and a camera module. The GPS module would help track a person's whereabouts and warn the wearer if he/she enters a hotspot. The camera module captures images of people who come closer than 4m to the person on being triggered by the proximity sensor. If a person comes closer than 2m, a buzzer warns the wearer. All imagery and GPS data is stored on a micro SD card which acts as a buffer and sends data to the AWS cloud. If the person is tested positive, the GPS data and the imagery data are analysed in the cloud using AWS IoT Core for identifying people at risk so that they may be quarantined in time.
If a person is found positive all people coming in close contact are automatically warned using AWS IoT events scripts with the webapp made on NodeRed.
# PSoC 6 Pioneer kit
# VL53L1X TOF distance sensor
# OV620 camera module
# Ublox Neo6M GPS module
# Connecting wires
Here, I have preferred the Pioneer board over the Prototyping kit over the Pioneer kit so that I can do sound proceessing based ML at the edge. For example if a person comes from behind I wish to do audio processing to recognise those footsteps...things current solutions totally ignore. I believe that though the Prototyping kit has more memory, the form factor of the Pioneer along with the power supply flexibility makes it a no-brainer
# WICED Studio
# Android Studio(for app)
Who am I
An AI and ML enthusiast from India with a deep interest in powerful MCUs taking edge computing to the next level. I have worked on several AI enabled IoT projects in the past. I am familiar with Arduino, Teensy, NRF and RasPi. I have used Wifi/BT and Lora in the past.
I have seen few MCUs like the PSoC 6 which are powerful enough to run AWS FreeRTOS and AWS IoT Greengrass inferences. I would love to use a Pioneer board to try this out.