Embedded Software for STM32 using LoRaWAN, Acconeer A121 and BLE
Budget: $750 – $1,500 CAD
I need an Embedded Software developer for my project that involves data collection and transmission using the LoRaWAN communication protocol. The ideal candidate should have experience and knowledge in:
- Embedded Software development for STM32 microcontrollers
- LoRaWAN protocol implementation
- Acconeer A121 sensor integration and control in measuring liquids from industrial containers
- BLE protocol expertise and experience
- MQTT Data transmission (using Cayenne)
- Integration with ThingsBoard
The primary function of the software is data collection and transmission, and the communication protocol priority is LoRaWAN. Additionally, the software should have the capability of monitoring battery levels. The ideal candidate should have experience in developing low power consumption software and be able to implement battery level monitoring as well as writing clean modular C code with an understanding of how to accomplish remote in the field firmware upgrades over slower unreliable networks. The transmission of the data will use MQTT leveraging Cayenne encoding and will integrate to a backend system running ThingsBoard.
- Embedded Software development for STM32 microcontrollers
- LoRaWAN protocol implementation
- Acconeer A121 sensor integration and control in measuring liquids from industrial containers
- BLE protocol expertise and experience
- MQTT Data transmission (using Cayenne)
- Integration with ThingsBoard
The primary function of the software is data collection and transmission, and the communication protocol priority is LoRaWAN. Additionally, the software should have the capability of monitoring battery levels. The ideal candidate should have experience in developing low power consumption software and be able to implement battery level monitoring as well as writing clean modular C code with an understanding of how to accomplish remote in the field firmware upgrades over slower unreliable networks. The transmission of the data will use MQTT leveraging Cayenne encoding and will integrate to a backend system running ThingsBoard.