Optronia
Highlights
- Real-time detection of wildlife via thermal imaging sensors
- Bluetooth-enabled control and configuration of mower-mounted sensors
- Automated alerts and GPS tagging of animal locations
- Offline data storage with synchronized map-based visualization
- Integrated system for logging, reviewing and managing detection events
Challenge
Optronia together with PÖTTINGER approached SoftTeco with a request to create a mobile application that would connect with optical infrared sensors, mounted directly on the mower. The goal was to create a system that could automatically detect hidden animals or nests in tall grass before mowing — a task traditionally performed manually and prone to human error. The solution needed to automate detection, improve response time and minimize harm to wildlife during field operations.
Solution
SoftTeco developed a native iOS application that communicates with thermal sensors installed on mowers via Bluetooth. When a sensor identifies an animal through thermal wave detection, the app immediately receives the data and processes it in real-time. The system not only records the detection but also triggers an in-app alert to the user. This warning allows the machine operator to pause operations, safely remove the animal or nest and log its location for future reference. Each detection is marked with a GPS pin and users can add custom notes or images linked to each event.
Sensor configuration, including sensitivity adjustment and placement settings — is handled directly within the app. Once a mower is connected, future connections are established automatically, ensuring a seamless user experience in the field. All data is stored locally using Core Data with an SQLite backend, enabling smooth performance even in offline environments.
Tech Stack
Mobile
Swift
CoreBluetooth
CoreLocation
CoreData
Combine
GoogleMaps
How it works
SoftTeco’s team was responsible for developing the iOS application from scratch. Since the application is connected to IoT sensors and processes the data in real-time, we needed a lightweight storage solution. We opted for the SQLite database engine wrapped in the Core Data framework by Apple.
As soon as the sensor detects an animal, the record about the animal’s location is stored in the database. For immediate and accurate location detection, our team used the Core Location framework. Users can also share these records and photos of animals via a preferred social network or via SMS messages. The application connects to mowers and sensors via Bluetooth. A user has to manually connect the app to the needed mower only once – after the connection is established, the app will automatically connect to this mower in the future. Configuration of sensors (sensitivity level, placement on the mower) is also performed via Bluetooth directly from the app.
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Results
The delivered application allowed Optronia to significantly improve the accuracy of animal detection during the mowing process and is now used by thousands of users in the farming industry across Europe. SoftTeco was glad to participate in this project and hopes to collaborate with the Optronia company again in the future.
