# A Low-Cost Remotely Configurable Electronic Trap for Insect Pest Dataset Generation
## 4 Discussion
Indeed, in a recent analysis of the strengths and weaknesses inherent in insect detection devices, it was highlighted that the prototype development has to follow key criteria such as a compact design, miniaturizing the electronic components, reducing final dimensions, and ensuring field maintenance-free operativity, together with high-quality, cost-effective, and widely available products, to facilitate large-scale production [40]. Our device aligns with these requirements, as it has been developed in a compact form factor (\(5\times 7\times 10\) cm), with a low cost (50 EUR) and low power consumption (120 mA in standard (non-sleeping) working mode). [PERSON] et al. [22] described a system based on the transmission of images to a remote service for classification. However, the hardware included in that work is much more complex and expensive than the one in this work. Similarly, [PERSON] et al. [23] developed a prototype of an intelligent trap within a limited budget (less than 375 EUR), basing their development on the EXPRESSIF ESP32 microcontroller, renowned for its low power consumption and compact design. Consequently, our results in terms of power consumption closely align with theirs, though our costs are lower and our system possesses the capability for remote reconfigurations, unlike previous systems. The proposed system demonstrates notable advancements in the field of remote insect monitoring, yet certain limitations inherently define its operational scope, presenting opportunities for further optimization. The device's reliance on specific operational modes impacts battery life, particularly in high-demand settings such as streaming mode, which may reduce operational autonomy. Nonetheless, this limitation is offset by the system's compatibility with external power solutions, including solar panels, which enhance field usability. Additionally, although stable network connectivity is required for real-time monitoring and remote reconfiguration, the system's low data transmission requirements make it feasible for deployment even in moderately connected rural settings. Regarding scalability, while continuous data collection across multiple devices could present data management challenges, the system's modular API-based architecture supports flexible data processing and storage that can be scaled with appropriate server resources as necessary. Lastly, although the study evaluated a limited selection of camera models, the device proved robust in controlled environments, establishing a practical foundation adaptable to a variety of field conditions. These considerations underscore the system's versatility as a low-cost solution with promising adaptability in pest management applications. This work presents a significant advancement in the field of IPM by leveraging digitalization to address the crucial challenge of reducing workload and enhancing decision-making accuracy. The remote reconfiguration capability of our system distinguishes it from previous studies, eliminating the need for on-site visits and allowing real-time adjustments to acquisition parameters. This capability not only aligns with recent trends in optimizing image acquisition for downstream processes but also provides enhanced flexibility and adaptability to diverse pests and environmental conditions. Our compact, low-cost, and low-power design meets essential requirements outlined in previous research, such as the need for a compact device with minimal maintenance during field deployment.