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--- amc:ss2024:schafalarm:start [2024/07/30 22:21] – [Second Prototype (ESP32-S3 with RFM69HCW and GY-521)] tasio.rodriguez-puy
+++ amc:ss2024:schafalarm:start [2024/07/30 22:26] (current) – [5. Conclusion] tasio.rodriguez-puy
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 ======4. Discussion ======
-The initial use of the Xiao BLE Sense showed that while it was capable of detecting motion and transmitting data via BLE, the range limitations and lack of roaming capability made it unsuitable for our needs. The range limitations might be able to be overcomed with the [[https://github.com/adafruit/Adafruit_BluefruitLE_nRF51|Bluefruit library]], but it was not possible to properly configure it and test it, so it remains unknown to which extent would have the range increased.\\
+The initial use of the Xiao BLE Sense showed that, while it was capable of detecting motion and transmitting data via BLE, the range limitations and lack of roaming capability made it unsuitable for our needs. The range limitations may be overcome with the [[https://github.com/adafruit/Adafruit_BluefruitLE_nRF51|Bluefruit library]], but it was not possible to properly configure it and test it, so it remains unknown to which extent the range would have increased.\\
 The switch to the ESP32-S3 microcontroller with the RFM69HCW radio module and the GY-521 accelerometer overcame these issues. The RF69 module provided a much larger range, and the ESP32-S3's deep sleep mode helped in reducing power consumption, making the system more viable for real-world use.\\
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 Power consumption is also a critical factor for this project. Since the sensors and communication modules will be attached to sheep, they need to operate efficiently on battery power. One of the solutions to further reduce the power consumption would be cutting of the power supply to the RF69 module when the esp32 in on deep sleep so more power can be saved.
 ======5. Conclusion ======
-In conclusion, while the project has made significant progress in developing a system to detect sheep movement and potential wolf attacks, several critical steps remain. Field testing is necessary to check the system's performance in real-world conditions. Incorporating Ultra-Wideband technology would allow to track sheep positions accurately. Additionally, the challenge of continuously receiving accelerometer signals from multiple sheep needs to be addressed to ensure the system's scalability. Finally, optimizing power consumption is crutial for the practical application of the system, ensuring that it can operate efficiently over extended periods. These next steps are crucial for moving the project from prototype to a fully functional solution.
+In conclusion, while the project has made significant progress in developing a system to detect sheep movement and potential wolf attacks, several critical steps remain unsolved. Field testing is necessary to check the system's performance in real-world conditions. Incorporating Ultra-Wideband technology would allow to track sheep positions accurately. Additionally, the challenge of continuously receiving accelerometer signals from multiple sheep needs to be addressed to ensure the system's scalability. Finally, optimizing power consumption is crutial for the practical application of the system, ensuring that it can operate efficiently over extended periods. These next steps are crucial for moving the project from prototype to a fully functional solution.