What We Do
We are a non-profit association, founded in 2014, with the aim of promoting scientific research and innovation in the country. We believe that through the development of research and innovation activities and the creation of capacity in business, industry and academic institutions, we will boost productive sectors with high value-added technological products and services.
Support for R&D&I activities
We formulate research and innovation projects for companies and provide specialist advice on intellectual property and technology transfer issues.
Capacity building
Developing courses for researchers and on-demand training in areas of knowledge related to computing, automation, agronomy and biotechnology.
Advice to universities and research centres
We assist in the preparation of normative documents related to R&D&I, as well as in the strengthening of the different areas of R&D&I management.
Members
Our team is composed of distinguished scholars, each holding a doctoral degree and demonstrating extensive experience in scientific research and technological innovation. United by a commitment to excellence, they advance knowledge, explore emerging frontiers, and contribute to meaningful developments that shape the future.
Rosario Medina Rodríguez PhD.
Computer Vision, Image processing
Gustavo Pérez Zúñiga PhD.
Automatization, Robotics
Hugo Alatrista-Salas PhD.
Geospatial analysis, Pattern Mining
Miguel Nuñez del Prado Cortez PhD.
Data Privacy, Big Data Analytics
Eduardo Fuentes Navarro PhD.
Smart farming, Animal science
Ivonne Montes Torres PhD.
Oceanography, Modelisation
Projects
The projects presented here are technology-based initiatives developed within the framework of smart farming. Each project has progressed through various stages of technological readiness, reaching maturity levels of up to TRL 7. These efforts have been supported by Peruvian funding programs and have involved close collaboration with other national research centers and universities, promoting multidisciplinary research and innovation. Together, these projects reflect our commitment to advancing applied science and creating impactful technological solutions for the agricultural sector.
The images were created using ChatGPT 5 and Microsoft Copilot (DALL-E 4).
Mobilscopio Low-cost intelligent microscope for detecting mastitis in cattle
DairyVet Real-time monitoring system for Sierra's production to cope with climate change
Fenoval Phenotypic evaluation of Brown Swiss dairy cattle using image processing
Fibroscopio Low cost microscope for analysing fibre composition in textile products
Mobilscopio
Project funded by FONDECYT, under contract number 254-2015-FONDECYT
Amount of the grant: 146 820.00 PEN (~43 800 USD)
The objective of this project is to develop a portable microscope that can identify and count somatic cells in cattle milk using image processing and machine learning algorithms. Studying somatic cells in cattle is important because it enables inflammation of the mammary glands to be identified. Specifically, a high somatic cell count may indicate inflammation in the animal's mammary glands. Therefore, our aim is to detect mastitis quickly and at an early stage.
Team members: Hugo Alatrista Salas, Miguel Nuñez del Prado, Eduardo Fuentes Navarro, Rosario Medina Rodriguez
DairyVet
Project funded by INIA, under contract number 156_PI
The project funded by INIA proposes an AI-based real-time monitoring system for dairy production in high-altitude regions of Peru, integrating computer vision, data analytics, and mobile technologies. The system enables continuous acquisition and analysis of productive and physiological indicators in Brown Swiss cattle, supporting adaptive decision-making under climate variability. The methodology was designed, implemented, and validated through field experiments in Puno and Lima, in collaboration with academic institutions and international development agencies.Team members: Miguel Nuñez del Prado, Eduardo Fuentes Navarro, Hugo Alatrista Salas. Developpers: Fedra Trujillano, Gabriel Jimenez, Kevin Barrera
FenoVal
Project funded by INIA, under contract number 156_PI
This study investigates the feasibility of automating partial phenotypic evaluation of Brown Swiss cows in the Peruvian Andean region using computer vision and deep learning. A cow detection model based on transfer learning with the MobileNet architecture was developed using the TensorFlow Object Detection API and integrated into a decision-support system. The resulting mobile application enables real-time detection and template-based classification to assess whether an animal exhibits Brown Swiss phenotypic characteristics.Team members: Miguel Nuñez del Prado, Eduardo Fuentes Navarro, Hugo Alatrista Salas. Developpers: Juliana Apumayta
Fibroscopio
Project funded by PROCIENCIA, under contract number 072-2021-PROCIENCIA
Amount of the grant: 350,000.00 PEN (~104 400 USD)
This project aims to develop a portable, low-cost fiber identification system that leverages micro-computing, computer vision, and artificial intelligence. The device will instantly classify the primary component of a fiber—such as synthetic, sheep wool, cotton, or alpaca—directly in the field. Designed for use in remote regions like the Peruvian highlands, this technology will empower alpaca producers and artisans by ensuring product quality, securing manufacturing processes, and strengthening their position in domestic and international markets through a simple, user-friendly software interface.
Team members: Hugo Alatrista Salas, Patricia Larios Francia (U.Lima), Andrés Condori (CITE Puno), Gustavo Pérez Zúñiga, Miguel Nuñez del Prado, Hunan Quispe Manotupa and Sui San Ching Donayre (master students), Eduardo Fuentes Navarro, Rosario Medina Rodriguez
Contact Us
We invite you to get in touch with our research center for inquiries, collaborations, or additional information about our projects and capabilities. You may reach us by email or telephone, and our team will be pleased to assist you.
