Non-Body Contact Thermometer with Voice Output Via Wireless Communication

Currently, thermometer has been widely used by the public. In general, thermometers are designed for people who have normal physical conditions, especially in the ability to see. Disabled people, especially blind people, will find it difficult to use the existing thermometer, especially with the current pandemic situation, which is likely to spread COVID-19 quickly. In connection with this problem, non-contact body temperature measurement is needed with sound output and a wireless system so that there is less possibility of exposure to disease. Therefore, this study describes a non-body contact thermometer with sound output via wireless. The purpose of this study concludes that Non-Body Contact Thermometers can be made with Voice Output Via Wireless to determine normal or hyper and hypo human body temperatures. Thus, this thermometer make it easier for those who have limitations to see and reduce exposure to covid-19 between patients and users. The method in this study employed MLX90614 as a sensor whose output is in the form of digital data, HC-SR04 as a trigger on the MLX90614 sensor, and DF player as a reader on data that have been recorded via Google and stored on the SD card, and XBEE module as transceivers of data to pc. Temperature testing was further conducted by comparing the module with a standard tool, that is a digital thermometer. The error obtained from the module at normal temperature is 0.98%, while the smallest error is 0.1%. Furthermore,  in terms of the hypo temperature, the largest error is 1.80%, while the smallest error is 0.42%. Last, at hyper temperature, the largest error is 1.75%, while the smallest error is 0.10%

Implementación de un Dron Anticolisiones Capaz de Seguir una Trayectoria Preestablecida para la Elaboración de un Mapa de la Tasa de Ocupación Vegetal en una Zona

Se implemento un sistema de vuelo no tripulado, el cual es capaz de detectar obstáculos y evitar colisiones. El drone es capaz de tomar imágenes para su posterior procesamiento con lo cual se logra obtener el porcentaje y tamaño de ocupación vegetal en las parcelas, mostradas gráficamente en una GUI en el programa de Matla

Platform Development for the Implementation and Testing of New Swarming Strategies

Gemstone Team SWARM-AISwarm robotics--the use of multiple autonomous robots in coordination to accomplish a task--is useful for mapping, light package transport, and search and rescue operations, among other applications. Researchers and industry professionals have developed robotic swarm mechanisms to accomplish these tasks. Some of those mechanisms or “strategies” have been tested on hardware; however, the technical requirements involved in fielding a drone swarm can be prohibitive to physical testing. Team SWARM-AI has developed a platform that provides a starting point for testing new swarming strategies. This platform allows the user to select vehicles of their choosing- either air, land, or water based, or some combination thereof- as well as define their own swarming method. Using a novel decentralized approach to ground control software, this platform provides a user interface and a system of computational “units” to coordinate drone swarms with a centralized, decentralized, or combination architecture. Additionally, the platform propagates user input from the master unit to the rest of the swarm and allows each unit to request sensor data from other units. The user is free to edit the processes by which each drone interacts with the environment and the rest of the swarm, giving them freedom to test their swarming strategy. The software system is then tested with a swarm of quadcopters using Software in the Loop (SITL) testing