Low-cost solution for monitoring assets on the go

Inside the context of the DIGEST project WP3, a significant contribution for a modular and low-cost system able to monitor different parameters such as Temperature, position, etc. has been built and tested. It represents a significant advancement in the field of environmental sensing and mobile asset monitoring, offering a low-power, long-range, and fully open-source IoT solution built on the ESP32-S3 platform. By integrating LoRaWAN communication, Bluetooth Low Energy (BLE), GPS, and onboard data visualization capabilities, the system addresses several of the limitations typically encountered in existing IoT deployments — particularly those involving mobile or remote assets.

One of the most notable contributions of this solution is its seamless support for mobile asset tracking. Thanks to the integrated GPS module and LoRaWAN’s extended communication range, assets can be monitored in motion across wide geographic areas — without relying on cellular connectivity or local Wi-Fi. This makes the system ideal for use cases such as monitoring the movement of equipment in logistics chains, supervising mobile environmental probes, or managing agricultural vehicles and tools in smart farming applications.

Moreover, the device’s energy-efficient design ensures that it remains operational over long periods, even in battery-powered scenarios — a critical requirement for mobile systems where constant recharging or maintenance is impractical. By providing real-time geolocation data alongside environmental metrics, the platform facilitates comprehensive situational awareness for mobile assets.

From a technological standpoint, the use of the ESP32-S3 microcontroller introduces advanced features such as AI acceleration and low-power sleep modes, enabling sophisticated edge computing scenarios directly on the device. The project also incorporates BLE for local configuration or data retrieval, and an OLED screen for quick on-site status checks, enhancing its usability and flexibility in the field.

Unlike many proprietary or siloed IoT offerings, this solution is fully open-source and modular, empowering developers, researchers, and integrators to tailor it to specific applications. It serves not only as a prototype but also as a reference architecture for deploying scalable, intelligent, and resilient mobile asset management systems.

In essence, this contribution bridges the gap between traditional static sensor networks and the dynamic needs of mobile environments, delivering a robust and extensible platform for intelligent asset tracking and environmental sensing in even the most challenging conditions.

More details, including code can be found under GPL license at https://github.com/jordieres/IoT-IoTA_PSI_2024.

Special acknowledge is due to Irene Pereda and PhD candidate Amir Farmanesh for their invaluable and tireless effort.