Aquaculture is carried out in controlled environments to guarantee the health, growth, and survival of aquatic species, so it is essential to monitor water quality parameters. We designed and implemented a system based on the Internet of Things for monitoring dissolved oxygen and temperature in Amazonian fish larviculture. We based the design of the architecture on four layers: data acquisition, communication, cloud server and application. We carried out the experimental tests with the data collected by the system during seven days of culture of larvae of the species Piaractus brachypomus (paco) in the aquaculture center “La Cachuela”. The values obtained for dissolved oxygen varied between 7.43 ± 0.04 and 7.83 ± 0.02 mg L-1; regarding the water temperature, it fluctuated between 19.59 ± 0.45 and 25.45 ± 0.11 °C. We concluded that the system developed for monitoring dissolved oxygen and water temperature displays data obtained in real time, in both cases the values are within the tolerable ranges for the cultivation of this species. La acuicultura se desarrolla en entornos controlados para garantizar la salud, crecimiento y supervivencia de las especies acuáticas, por lo que resulta clave monitorear los parámetros de calidad del agua. Diseñamos e implementamos un sistema basado en Internet de las Cosas para monitoreo del oxígeno disuelto y temperatura en larvicultura de peces amazónicos. Basamos el diseño de la arquitectura en cuatro capas: adquisición de datos, comunicación, servidor de nube y aplicación. Realizamos las pruebas experimentales con los datos recolectados por el sistema durante siete días de cultivo de larvas de la especie Piaractus brachypomus (paco) en el centro acuícola “La Cachuela”. Los valores obtenidos para el oxígeno disuelto variaron entre 7,43 ± 0,04 y 7,83 ± 0,02 mg L-1; en relación con la temperatura del agua esta fluctuó entre 19,59 ± 0,45 y 25,45 ± 0,11 °C. Concluimos que el sistema desarrollado para monitoreo de oxígeno disuelto y temperatura del agua visualiza datos obtenidos en tiempo real, en ambos casos los valores se encuentran en los rangos tolerables para el cultivo de esta especie.

Acute malnutrition affects 3.1% of children under five years of age in Amazonian communities in Peru, where limited access to health services constrains timely nutritional assessment. In this context, this study aimed to develop, implement, and evaluate NutriRadar, a mobile application for automated childhood nutritional classification based on the anthropometric standards of the World Health Organization (WHO). The application was developed using a waterfall software development methodology and implements the calculation of the Weight-for-Height Z-score (WHZ) from basic anthropometric variables (weight, height, age, and sex). NutriRadar was designed with offline functionality, deferred data synchronization, and compatibility with low-end mobile devices to support operational use in Amazonian settings. Field validation was conducted in two early childhood education institutions in Puerto Maldonado, Peru, and included anthropometric assessments of 75 children aged 3–4 years. The application demonstrated stable offline operation, response times suitable for clinical practice, and nutritional classification results equivalent to the WHO Anthro reference tool. NutriRadar represents a viable and reproducible digital automation solution for the operational application of a deterministic WHO anthropometric protocol, contributing to the reduction of operational errors and strengthening standardized nutritional assessment in resource-limited Amazonian contexts.