Conference Agenda

This study aimed to design and evaluate a low-cost, open-source, intelligent irrigation system to optimize water use in small-scale agricultural settings in the Cajamarca district. The project developed a functional prototype comprised of humidity and temperature sensors, an Arduino UNO R3 microcontroller, and actuators such as a water pump and a ventilation system. An experimental methodology was employed in a simulated controlled environment to verify the system's accuracy in activating irrigation only when humidity fell below predetermined thresholds.

The results demonstrated that the system maintains substrate moisture within appropriate ranges and reduces manual intervention, showing an estimated savings of 20% to 30% compared to traditional irrigation methods. These figures align with national and international studies on precision agriculture, reinforcing the prototype's potential as an accessible technological solution for optimizing water consumption. Furthermore, it was confirmed that the use of Arduino-based technologies represents an economically viable alternative for rural communities, facilitating the gradual adoption of practices associated with Agriculture 4.0.

In conclusion, the developed prototype constitutes a proof of concept that validates the technical functionality of smart irrigation using sensors. The research demonstrates that it is possible to develop accessible and replicable automation tools capable of promoting more efficient and sustainable water management in future, larger-scale projects.

This study was conducted in Cajamarca, focusing on milk storage tanks and simulating them using CADE SIMU and ProModel. The overall objective was to simulate an automated level monitoring and notification system using Arduino and ultrasonic sensors. The methodology consisted of a quasi-experimental simulation-based design, building the electronic model in CADE SIMU and the filling process in ProModel, analyzing time scenarios, and exporting data to Excel. The results, according to the specific objectives, demonstrated: problems with manual control such as overflows and weekly losses; 97% accuracy of the ultrasonic sensor in the simulation; and an 85% reduction in overflows and an 87% reduction in losses with the automated system. In conclusion, it was validated that automation improves storage efficiency, reduces human error, optimizes filling times, and proves to be a viable and effective solution for the dairy industry in Cajamarca.

This study presents the design and implementation of an automated system for the efficient sorting of Persea americana (avocado) in the city of Cajamarca, Cajabamba province, Condebamba district. The objective is to replace the traditional manual process, which is characterized by high variability, errors due to visual fatigue, and high operating costs. The research was conducted in four phases: diagnosis of the manual process, design of the automated prototype based on machine vision and mechanical control, comparative performance evaluation, and economic analysis. The proposed system integrates a conveyor belt, ultrasonic sensors, and pneumatic actuators, allowing the fruit to be sorted according to size, ripeness, color, and surface defects. The results show significant improvements: a 58.7% reduction in processing time, a 79.7% decrease in errors, a 96.2% increase in accuracy, and a 142.4% increase in production capacity. The economic analysis demonstrates a payback period of 1.29 years and a 49.7% reduction in operating costs. It is concluded that automation is technically and economically viable, improving the competitiveness of the agro-industrial sector and aligning with the principles of Agriculture 4.0.

Abstract- In the Cajamarca region, an important agro-industrial area in Peru, manual fruit harvesting continues to face significant limitations in operational efficiency, harvest time, and post-harvest damage caused by inadequate handling. These issues reduce product quality and undermine producers’ competitiveness. To address this challenge, the present project develops an adaptive robotic arm as a technological solution to optimize fruit harvesting and minimize losses. The introduction highlights the need for automated systems that enable more precise, safe, and efficient fruit manipulation.

The main objective is to evaluate the impact of the prototype on improving efficiency, product care, and risk reduction compared with traditional harvesting methods. The project involves designing the robotic arm, assembling its electronic components, programming its control system, and analyzing its performance through functional and operational tests.

A pre-experimental methodology was applied, including CAD design, 3D printing of structural components, integration of MG995 and MG900S servomotors, flexible sensors, and an NRF24L01 wireless module connected to an Arduino board. The prototype was then calibrated and tested under controlled conditions.

The results showed that the robotic arm successfully adapted to fruits of various sizes and textures, reducing pressure-related damage, improving grip precision, and optimizing harvest time. Additionally, the wireless communication system ensured stable and synchronized operation across components.

In conclusion, the developed system represents an innovative and sustainable alternative for agricultural automation in Cajamarca. It contributes to the modernization of the sector by providing an efficient solution that reduces reliance on manual labor and enhances the quality of harvested products.

This work presents the design, simulation and validation of a low-cost temperature monitoring system based on Arduino and the DHT-11 sensor, oriented to the cold chain in small cheese factories in Cajamarca dedicated to the production of buttery cheese. Faced with the problem of precise and continuous thermal control, which affects the quality and safety of the product, a prototype was developed that records temperatures in real time, visualizes data on an LCD screen and activates automatic alerts in the event of critical deviations. The methodology included selection and characterization of the DHT-11 sensor (range 0-50°C, accuracy ±0.5°C, low cost), construction of the electronic circuit with accessible components, programming for data logging and alerts, and evaluation in a simulated environment. The results demonstrated significant quantitative improvements: reduction of the margin of error by 80%, increase in measurement frequency by 1,800-5,400 times and decrease in the risk of cold chain breakdown by 90%, with economic savings of 60-70% and stability in 94% of trials. The comparison with traditional methods showed superiority in precision, efficiency and accessibility, confirming technical and economic viability for small companies. The modularity of the design allows future expansions with IoT, strengthening local competitiveness and preserving the quality of perishable products.

Abstract—This paper describes the redesign of an intelligent firefighter helmet prototype aimed at enhancing safety during wildfire suppression in Honduras. Building upon a base system that monitors vital signs (heart rate and blood oxygen), ambient temperature, posture, and location via LoRa technology, the enhanced design integrates several key improvements: a high-speed calibration GPS module, carbon monoxide (CO) detection, and ruggedized thermal and waterproof housing for the electronic components. Furthermore, a redesigned monitoring interface presents both quantitative and qualitative data to provide comprehensive situational awareness for the user and command center. Experimental results demonstrate a GPS accuracy of ±2.5 m, reliable hazardous gas detection, and structural integrity at temperatures up to 85°C. This system improves occupational safety and emergency management by providing real-time data for informed strategic decision-making in wildfire scenarios.