The Development and Evaluation of an Automated System in Detecting Environmental Data for Monitoring Forest Activity

Abstract

Forest ecosystems have always received worldwide attention due to their biological diversity and these forests are vital for human existence since their area is decreasing due to human negligence and over-exploitation by the human population. Recent reports showed the evidence of illegal logging and harvesting activities, detected late, thus coming up with serious consequences. Therefore, an early detection system must be developed to monitor these illegal activities by collecting the environmental data. This research characterized the dynamics, cycle of temperature, humidity, and phase particle based on the conceptual framework that has been developed. The ADDIE model was selected as the proper model to be implemented in developing the prototype. The sensing data has been identified as a salient data for preserving the forest ecosystem that must be protected as part of the population well-being and prolong heritage. The hardware components for designing this prototype consisted of temperature and humidity sensor, Solar LiPo Rider for self-powering device, and phase particle sensor. This prototype also allows for writing and simple erasing the main programming through USB port when connected to a computer. The data can also be collected via UART and can be displayed on the monitor for further analysis and monitoring the ecosystem. Therefore, the development of this automated object-based change detection system will be useful and beneficial in assisting regulatory bodies, researchers, and ecologist for identifying the changes within the ecosystems. Finally, the data gathered will be evaluated using a GraphPad Prism 6 software to compare the result of the data gained from both the Meteorological Weather Measurement Devices and the automated system for detecting environmental data (ASDE) to see whether the data collected by the prototype are precise and accurate.