Ex Machina is a weather analytics and industrial IoT company, that offers forecasting services to the energy industry. The company uses a unique combination of highly accurate weather and energy data, weather sensors technology, and AI to deliver its market-leading services.
Within the scope of Agile IoT project, Ex Machina effectively progressed its smart gateway hardware which is a critical component in the company’s industrial IoT energy forecasting solution.
Gateway Ex Machina (GatewayXM) extends and integrates Agile IoT technologies with the open source Thingsboard IoT platform and the Espressif ESP32 low power system on chip (SoC), effectively creating the necessary technology for an industrial grade robust gateway. This is combined with wireless sensors that can be used in any industrial IoT project. The result is a IoT solution that requires minimal maintenance and can be easily deployed on the field and start producing useful data with little configuration and quick setup times. Additionally, , wireless ESP32 mesh technology has been adopted, enabling a plethora of sensors to act as sources for the collection of data in remote areas where AP WiFi network coverage is low. Due to ESP32’s low cost and ease of deployment, there is now possibility for large-scale deployments and data acquisition.
Using the resin.io platform, a part of the Agile IoT ecosystem, fleets of GatewayXM devices and their ESP32 wireless sensors can be entirely managed and updated remotely, including the ability to push OTA updates to all the connected ESP32/8266 mesh sensor nodes.
The achieved goals of the delivered open source solution include the following: the instructions and source-code on how to effectively utilize Eclipse Kura and connect to MODBUS smart meter devices, the integration of Eclipse Kura with Thingsboard.io and the communication telemetry from MODBUS devices on the field to the Thingsboard cloud server, the enablement of easy remote device management and OTA software update of GW software through utilizing dockerized Kura, resin.io, and other AGAIL technologies.
Furthermore, there are provided instructions and source code on how to develop an ESP32 mesh sensor network particularly bridged with the GW. This enables sensor telemetry data to be forwarded to Thingsboard server including the ESP32 firmware OTA capability via GW.
All of the above information can be found on Ex Machina public repository at github.
Ensuing the success of this Agile IoT project, Ex Machina is currently building a unique industrial grade, solid-state weather station that is designed for large-scale dense network deployments.This hardware enhances Ex Machina’s cloud platform ability to forecast weather and weather-sensitive resources like energy, by providing hyperlocal weather conditions. If you would like to find out more about how hyperlocal weather insight can help your weather sensitive business, contact us via: email@example.com.