This project is part of an assignment for the course of Internet of Things at the Sapienza University of Rome. The aim is to build a Virtual Environmental Station based on Amazon Web Services (AWS) that simulates some sensors (Temperature, Humidity, Rain Height, Wind Direction and Wind Intensity) generating random values in several ways and sending them to a database, AWS DynamoDB, with an MQTT broker. Then these data will be shown on a simple web application (running in localhost for this project).
The environmental data are generated by a Python script.
You can find the script at virtual_stations/environmental_station_simulator.py
You can find the manage.py to run the localhost page at django_web/manage.py
- Reference: http://ichatz.me/Site/InternetOfThings2020-Assignment1
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The environmental data are generated by two RIOT devices and sent to AWS with an MQTT-SN\MQTT transparent bridge.
You can find the RIOT file at emcute_mqttsn/main.c
You can find the transparent bridge at mqttsn_client/bridge.py
You can find the manage.py to run the localhost page at django_web/manage.py
Attention: if you clone this repository you may have to do some paths adjustments. For further information give a look to the guide on Hackster
- Reference: http://ichatz.me/Site/InternetOfThings2020-Assignment2
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The environmental data are generated by two RIOT devices that stand on IoT-Lab real devices, sent to The Things Network through the LoRaWAN protocol and forwarded to AWS IoT Core and DynamoDB thourg a TTN/AWS bridge.
You can find the RIOT file at lorawan_station/main.c
You can find the bridge at lorawan_station/TTNbridge.py
You can find the manage.py to run the localhost page at django_web/manage.py
Attention: if you clone this repository you may have to do some paths adjustments. For further information give a look to the guide on Hackster
- Reference: http://ichatz.me/Site/InternetOfThings2020-Assignment3
- Hackster guide
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- LinkedIn profile
This project is part of an assignment for the course of Internet of Things at the Sapienza University of Rome. The aim is to build a Crowd Sensing application based on Amazon Web Services (AWS) that determines through, the smartphone's accelerometer, the user activity. The analysis of the data provided by the accelerometer will be operated in two ways: edge-based and cloud based.
You can find further information in crowd_sensing folder
- Reference: http://ichatz.me/Site/InternetOfThings2020-Assignment4
- Hackster guide
- YouTube video
- LinkedIn profile