LOW COST REAL TIME AUTONOMOUS REMOTE MONITORING PLATFORM
Joseph Rodriguez1, Pedro M. Maldonado1, Lora Harris2, Jamie Pierson3.
1Universidad Metropolitana, Puerto Rico, San Juan, PR, 2University of Maryland Chesapeake Biological Laboratory, Solomons, MD, 3Horn Point Laboratory, University of Maryland Center for Environmental Science, Cambridge, MD.
Environmental scientists have a need for gathering multiple parameters during specific time periods to answer their research questions. Most available monitoring systems are very expensive and closed systems, which limits the potential to scale up research projects. We developed a low cost, autonomous, real-time monitoring platform that is both open hardware/software and easy to build, deploy, manage, and maintain. The hardware is built with off-the-shelf components and a credit card sized computer called Raspberry Pi, running an open source operating (Raspbian) system. The system runs off a set of batteries and a solar panel, which makes it ideal for remote locations. The software is divided into 3 parts: a framework for abstracting the sensors (initializing, pooling, and communications) designed in python and using a fully object-oriented design, making it easy for new sensors to be added with minimal code changes; a web front-end application for managing the entire system; and a data store (database) framework for local and remote data retrieval and reporting services. Connectivity to the system can be accomplished through a wi-fi or cellular internet connection. Scientists are being forced to do more with less, in response, our platform will provide them with a flexible system that can improve the process of data gathering with an accessible, modular, low-cost, and efficient monitoring system. Currently, we are waiting for permits from the Department of Natural Resources in Puerto Rico to be able to deploy the platform at the Laguna Grande Bioluminescence Lagoon in Fajardo, PR.