Implementation of Wireless Sensor Networks to Prevent Deforestation Using Node MCU

Abstract

The illegal movement of valuable trees such as sandal wood trees in forests poses a severe risk to natural reserves and it instigates a great loss to our country’s wealth. Almost 24,000 square miles has been lost due to deforestation in the past decade. This paper proposes an antipoaching system using NodeMCU based wireless system that uses 3- axis MEMS accelerometer (GY-61) and tilt sensor for detecting the falling of trees due to cutting of trees or natural calamities and Flame sensor, fire retardant for detecting and controlling the fire. In this project we use NodeMCU which has an inbuilt Wi-Fi module which covers a distance of around 300m range, is used in this project for cost efficiency and also NodeMCU enables the communication with neighbor nodes like client and server nodes. This protocol is used to monitor the trees even using a single node from the server system. The solenoid valve is used to spray the fire retardant to control the fire. Some IOT modules can also be used in this system to provide accurate information and remote monitoring of trees.

Participatory design of a smart forest in the Brazilian Amazon using smartphones, algorithms, and ethnographic methods

“…However, at the time of writing in 2022, they have not arrived as expected. Special wireless networks can be built, as in scientific research and top‐down forest management (DeBell et al., 2019; Molina‐Pico et al., 2016; Sivasankari et al., 2020), but that would take additional expertise, equipment, and funding. One alternative that community residents suggested is to have people routinely climb the trees, switch data chips in the installed smartphones weekly or monthly, and carry them to communities with Internet access for data transfer.…”

“…Results would be immediately reported to the Amazonas state government and the Brazilian Institute of the Environment and Renewable Natural Resources, 2 enabling them to investigate and intervene more quickly and at less expense than is currently possible given their limited capacity for detection by satellite or aerial imaging. According to the reserve managers and environmental researchers we interviewed, digital acoustic detection could be also more sensitive, efficient, and economical than other forest-monitoring technologies, such as tilt sensors (Sivasankari et al, 2020), which work only for the particular trees on which they are installed. Reserve managers with knowledge about carbon markets told us that digital acoustic detection would also be more timely and less costly than the on-site verification required by REDD+ projects and could serve at least as a supplementary method of carbon-storage monitoring to enhance carbon investors' interests and trust.…”