# A Low-Cost Remotely Configurable Electronic Trap for Insect Pest Dataset Generation
## 5 Conclusions  
This work provide an efficient working prototype to be deployed for insect pest monitoring. Several advances have been included compared to the current insect pest monitoring devices described in the scientific literature. Some monitoring devices take photos and count the number of detected insect from a given type. In those cases in which there are remote communications, only one number is sent from the device to the server. No visual evidence is stored to confirm these values. Thus, these systems cannot detect other insects unless they are stopped and updated one by one with new detection models. On the other hand, the present prototype would enable the remote detection of more insects, as it would feed remote repositories with images of the real insects attached to the trap and new models could be developed. Other monitoring systems take photos and sent them to a server, but working parameters cannot be updated. Therefore, our proposal is an advanced monitoring system, in which the device can take photos with the best parameters for that environment and time, as they can be remotely updated. The device has been built using low-cost components, which makes the final product economically affordable. Moreover, it has been proved that the device has a low energy consumption profile, which makes it suitable for deployment in the fields with batteries or renewable sources, such as photovoltaic panels. We have tested the prototype for power consumption, showing that the current is the range of 120 to 200 mA in standard (non-sleeping) working mode without sending images to the server and rising to 350-400 mA when uploading images, for few seconds, at most. Nevertheless, the frame uploading can be configured to be carried out fewer times so that this current profile can be extended for long periods of time. The most relevant and distinctive feature that sets this insect pest monitoring system apart from others, as highlighted in the scientific review, is its remote management capability. The system communicates with the server through a standard Web API, making it easy to upgrade and enhance. Additionally, this setup allows for bidirectional communication, enabling the updating of execution modes and working parameters of the electronic trap device. In this work, three compatible cameras (two versions of the OV2640 cam, with 2 Megapixels, and the other, OV5640-C, with 5 Megapixels) have been tested and analyzed. The results suggest, as expected, that the OV5640-C provides slightly better overall values than the other cameras. An objective quality evaluation has been carried out to determine the response of the cameras with different metrics. Therefore, these results prove the technical viability of a low-cost IPM system with remote management, providing the best visual evidence. Hence, the present prototype allows for the acquisition of a large dataset of different insect pests, which would help to tune the detection models with more insects, providing higher levels of accuracy and precision. Future improvements could focus on enhancing energy efficiency and scalability to broaden the system's applicability across various operational contexts. One effective way to improve energy efficiency is by utilizing the microcontroller's low-power mode, which could significantly reduce energy consumption. However, implementing this feature may add complexity to the reconfiguration protocol, potentially requiring scheduled communication windows or alternative triggers to prevent a continuously open communication channel. This strategy would support energy efficiency while maintaining the device's remote configurability. Regarding scalability, we find it interesting to deploy electronic trap networks while adhering to a low-cost philosophy. This can be achieved through local hierarchical networks using technologies like LoRa 2.4 GHz or similar, which provide reasonable coverage in rural environments. Such a network architecture would enable large-scale deployment without the need for extensive infrastructure.