IoT GPS Tracker with Movement Alert and LoRaWANObjectives:
Read more- Obtain the precise GPS location of the device in real-time.
- Detect device movement using an accelerometer.
- Send location and movement status to a cloud platform via LoRaWAN and The Things Stack for long-range tracking.
- Configure alerts when the device moves unexpectedly or enters/exits a defined geographical zone (geofencing, if the platform supports it).
Objective Level: Intermediate
Prerequisites:- Fundamentals of Arduino (C/C++) programming.
- Basic concepts of electronics.
- Familiarity with the Arduino IDE or PlatformIO development environment.
- Understanding of LoRaWAN communication and The Things Stack operation.
- Basic knowledge of GPS systems and IoT platforms with mapping capabilities.
- WISBLOCK Base: RAK19003 Mini Base Board (for a compact and portable design)
- WISBLOCK Core: RAK4630 Nordic NRF52840 (with integrated LoRaWAN for long-range communication)
- WISBLOCK Sensor: RAK12033 IM-42652 6-axis Accelerometer
- WISBLOCK Miscellaneous: RAK12500 ZOE-M8Q GNSS GPS Module
- Other Components / Accessories:
- RAK7268V2 WisGate Edge Lite 2 (LoRaWAN Gateway)
- Battery Connector Cable
- Screwdriver
- Arduino IDE or PlatformIO
- Arduino libraries for RAK modules (e.g., RAKwireless_RAK4631_BSP) and specific libraries for GPS (e.g., TinyGPS++, SoftwareSerial if the GPS uses non-hardware UART pins) and accelerometer (e.g., SparkFun_ICM-20948_Arduino_Library or similar).
- Configuration software for the RAK7268V2 gateway.
- Account on The Things Stack (for the LoRaWAN network) and a cloud IoT platform with mapping capabilities (e.g., Ubidots, Datacake, Cayenne MyDevices).
Estimated Duration: 7-11 hours.
Learning Outcomes:- Ability to implement a real-time GPS tracking system.
- Skill in detecting and reacting to device movement.
- Mastery of transmitting location data via LoRaWAN, optimizing the payload for coordinates in The Things Stack.
- Knowledge in visualizing geographical data on IoT platforms and configuring geofencing.
- Experience in optimizing power consumption for portable battery-powered devices.
- Hardware Assembly: Connect the RAK4631 (Core) module to the RAK1903 (Mini Base Board). Connect the RAK12500 GPS module and the RAK12033 accelerometer. Connect the battery cable.
- Development Environment Configuration: Install Arduino IDE/PlatformIO and support for the RAK4631 board. Install the necessary libraries for the GPS and accelerometer.
- Node Programming (RAK4631):
- Write code to initialize the GPS module and obtain coordinates (latitude, longitude, altitude).
- Configure the accelerometer to detect movement (e.g., using a threshold for acceleration change or activity/inactivity detection).
- Implement logic to send GPS data and movement status via LoRaWAN. It is recommended to send data only when there is movement or periodically if static.
- Optimize power consumption: put the GPS module in low-power mode when constant reading is not needed, or turn it on and off intermittently. Use the microcontroller's deep sleep mode.
- Gateway Configuration (RAK7268V2): Connect the gateway to the network and configure it to connect to The Things Stack.
- The Things Stack Configuration:
- Access The Things Stack console.
- Register the Gateway: Add the RAK7268V2 gateway.
- Create an Application: Create a new application.
- Register the Device (RAK4631 Node): Register the device with its LoRaWAN credentials.
- Configure the Payload Formatter (Decoder): Write Javascript code to decode the GPS coordinates and movement status from the binary payload into a JSON object. The Things Stack has direct integrations with mapping platforms that can use this data.
- Integrate with the Cloud IoT Platform: Add an integration (e.g., "Webhook" or "MQTT") to an IoT platform with mapping capabilities (e.g., Ubidots, Datacake).
- Testing: Test the device outdoors to ensure good GPS signal acquisition. Move the device and verify that the location updates on the map and that movement alerts are triggered as expected.
- GPS Signal Acquisition: The GPS module may take time to get an initial fix (known as a "cold start"), especially indoors or with poor sky visibility. Always test outdoors.
- GPS Accuracy: GPS accuracy can vary (from meters to tens of meters) depending on signal quality and the environment. For higher accuracy, techniques such as averaging readings or filters can be used.
- GPS Power Consumption: The GPS module is one of the most power-consuming components. It is crucial to implement aggressive power management strategies (e.g., turning on the GPS only for a few seconds to get a reading and then turning it off) to extend battery life.
- Geofencing: Implementing geofencing can be complex. The logic can reside on the device (requires more processing and memory) or on the cloud platform (simpler, but requires the device to constantly send data for the platform to evaluate the position).
- The device obtains and transmits GPS location accurately and reliably.
- The accelerometer consistently detects movement.
- Location data is correctly visualized on a map in the IoT platform.
- Movement or geofencing alerts are triggered as expected.
- Battery life is acceptable for the intended use case (e.g., several days or weeks on a single charge).
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Teacher at Maude Studio & Erasmus+ project member: "Developing Solutions to Sustainability Using IoT" (2022-1-PT01-KA220-VET-000090202)
Thanks to Jose Miguel Fuentes.
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