# InoT Sensor Network for Wild-Animal Detection near Roads
## 4 Experiments  
For experimental research, the first batch of DSNs (eight units) was produced with slightly different angles of placement of the sensors in relation to the road (inclination of the side sensors from the road \(-5\) and \(-15\) degrees) and also with a rain cover installed  
Figure 8: Panasonic Eneloop pro battery discharge test results at 20 \({}^{\circ}\)C and 0 \({}^{\circ}\)C. Voltage jump in the green graph is the moment of measuring the battery’s internal resistance and recovery parameters. over one of the side sensors. Sensors were installed on the Kaunas-Sakaiai (41 km) road section (Figure 9) for one month. A photo camera was installed next to the DSN8 sensor. It is triggered by sensor activations. A wireless network is formed between the sensors and the camera using LoRa technology. When at least one of the sensors is triggered, the camera captures three photos at 200 ms intervals. Photos are stored in the camera (SD card). The camera provides an opportunity to view low-resolution photocopies that are placed in the camera manufacturer's database. To collect statistics and monitor the current situation in real time, a gateway based on Rpi4 was made. The gateway is connected to the sensor network using the LoRa technology, and a 4G modem was used for real-time monitoring. It was possible to connect to the gateway remotely and download the accumulated database. Physically, the gateway is placed 500 m away from the road section on the premises of the Sutkai Forestry. The first batches of DSNs were tested from July to October 2022. During the first weeks of monitoring, 10 sensor activations on average were recorded during the dark period of the day. Analyzing the camera images, several captured animals were found. Example photos (evening/night) are shown in Figure 10.  
From the provided sample photos, we can see that, in the dark, the camera allows for capturing objects up to 30 m away from its installation location. Therefore, the verification of the reasons for the activation of DSN sensors becomes problematic. It was observed that most of the triggers were caused by the rear PIR sensor rather than the side ones. The most likely reason for this could have been grass, tree, and shrub branches moved by the wind. Since only a small area of the roadside is maintained (moving, snow plowing), and the forest is only a few meters away from the roadside-marker post, it was decided to abandon this sensor, providing only the option for the installation of the rear PIR sensor unit in the following DSN versions. As expected, the sensors' work was also affected by environmental conditions: rain, contamination of the sensors' optics and taller grassy plants growing near them. It was observed that the DSN with a canopy over the PIR sensor optics, contrary to expectations, got significantly dirtier (dirt is not easily washed away by rain: see Figure 11). Figure 10: Photos of the detected wildlife. Figure 9: DSN installation positions near the road. After the tests of the first DSN generation, it was decided to modify the detection and signaling units to some extent:  
* The rear PIR sensor was removed, leaving only the possibility of additional installation of a separate submodule;
* The finally selected optical angle of the side sensors is equal to \(-5\) degrees in relation to the road line. Such an angle allows you to avoid the detection of passing cars and does not deviate too far from the side of the road;
* The Fresnel lens of the side PIR sensors has been changed from black to white (the entire DSN remains white: see Figure 12);
* Red LED signal indicators are aligned with the PIR optics unit, where the Fresnel lens also performs the function of an optical signaling window.