ElephantEdge tracker: Designing the firmware and first prototype solution

For the past two months, IRNAS and Smart Parks, in partnerships with Hackster.io, have been working on building the next generation OpenCollar ElephantEdge tracker, closely looking at requirements and features that make this a success. Two key concepts are driving it, rock-solid field performance and an intuitive user experience. In the previous blog and webinar, we did a deep-dive into the technical choices made in the design process and the experiences shared by Smart Parks, we hereby look deeper into the firmware and workflow aspects.

Together, we make sure to deliver sustainable, future-proof solutions. This requires a skillful integration of the latest technologies with years of development experience and a very agile hands-on process with the users, such that we converge to the best solution in the shortest amount of time.

Hackster.io will announce the contest winners of the ElephantEdge campaign on November 18th. With this campaign, we have called on the community to build ML models using the Edge Impulse Studio and tracking dashboards using Avnet’s IoTConnect, which will be deployed onto 10 production-grade collars. We will also report on this soon, so keep following us!

Development update

  1. Mechanics
  2. Electronics
  3. Firmware
  4. Smartphone Application

We strive to reduce the complexity of each while adding as many features as possible.


The current design has been field-proven on the previous generation of OpenCollar Elephant trackers and is at the moment undergoing mostly internal design changes to support the electronics, as well as externally adding the new required features. The only bigger change we are planning, is to make a somewhat bigger version to increase the space for extra battery capacity, which may be nice to have for specific high-resolution sensors applications. The next step upon validation of electronics and antennas is the manufacturing of field-deployable units to test.


The open nature of the design means that we have paid special attention to selecting the form-factor which supports the reuse for other tracking applications. The tracker size — in most cases — is driven by battery dimension. Typical sizes of round battery cells that are being used: 14250, 17500, 18500 and 18650. Therefore, an optimal format is defined by a number of these cell-types combined in parallel, where most cases of long-term tracking require at least two cells. For size comparison look at the Smart Parks Rhino trackers we have designed for size-constrained applications.

For ElephantEdge, we now have a compact form factor of 35mm by 50mm, comprised of the sensors, connectivity, storage and processing capabilities with integrated GPS and multi-band antennas supporting BLE, LoRa and WiFi, along with connection options for larger antennas, for example, to support Lacuna.space connectivity.

The current design is in the assembly process and will undergo extensive lab and field testing in the coming weeks.


The Zephyr Project is a scalable real-time operating system (RTOS) supporting multiple hardware architectures, optimized for resource-constrained devices, and built with security in mind. The Zephyr RTOS is based on a small-footprint kernel designed for use on resource-constrained systems such as animal trackers. It prioritizes the system layer for IoT terminal devices such as sensors, wearables, and other small connected objects.

Besides having good tracking and location features, one of the most important functions of the device is configuration and data collection. This is what separates good products from the bad ones, as users will interact with the device on a daily level. Since these trackers will be deployed in remote and hardly accessible places, we have learned that users need to be able to get the data and configure the device from a central and safe place. Devices are equipped with short and long-range wireless transceivers, Bluetooth LE and LoRaWAN. Having that in mind, we have built the configuration system such that it is accessible from all available communication streams. When devices are produced in the factory or reprogrammed in the field, a technical person in the team can easily change the settings JSON file and build the new release of the software. Knowing that not all users have the technical background, we have made the device setting configuration accessible to the user via mobile and web applications. Using a mobile application, users will be able to connect to the device via BLE and access its command and settings list where they can change everything locally being close to the animal wearing the tracker. On the other hand, sometimes it is necessary to do this remotely and that is why it can be done over LoRaWAN (generally exposed to users by a web application like Avnet’s IoTConnect).

The firmware is currently in Alpha stage with communication, data acquisition and processing features, being extended with user-features and detection mechanisms. In the next version, we will also work towards full integration with EdgeImpulse, to enable all these great use-cases we are looking for.

Smartphone application

Upon a review of technologies, React Native has been chosen as the framework enabling cross-platform app development with BLE support and a programming language supporting binary data operation, which significantly simplifies the communication with devices.

With the guiding principle of designing around a wireless communication, a custom schema has been put in place, which enables higher bandwidth operations via BLE as well as via LoRaWAN (network permitting). To ensure the user can read all important data from the tracker using the app, a JavaScript communication decoder is made available within the smartphone app. When the most important features are stable, we will also spend some iteration on design.

The application is currently in Alpha stage, offering a communication stack with implemented data transmission features, and the overlying user interface is now under design as the user workflows are being tested with the trackers.

We are getting there

We are applying today’s knowledge to create systems for an open future.

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