PLANTS MONITORING SYSTEM BASED ON WIRELESS SENSOR NETWORKS FOR GREENHOUSE APPLICATION

• Main Author: ALIYYA MACHFUD (NIM 23205342), ADAM
• Format: Theses
• Language: Indonesia
• Online Access: https://digilib.itb.ac.id/gdl/view/7007
• Institution: Institut Teknologi Bandung

Recently, wireless communication technology has developed rapidly so that we can communicate at almost any place on earth. Indonesia, as an agricultural country, faces many problems related with farming management system. In order to overcome that problems, this plants monitoring system, using wireless sensor networks technology, is designed as the alternative solution. Application of this system in vegetables greenhouse, has been chosen to simplify the system testing and characterization. Wireless sensor network (WSN) is an integrated system consists of wireless distributed and connected sensor nodes in a network topology and performs information sharing based on its application. Using cross-layer approach, the system, which is designed with clustered network topology for one greenhouse, consists of sensor node in the physical layer and TDMA-based (Time Division Multiple Access) MAC (Medium Access Control) protocol in the data link layer. The sensor node consists of sensor and signal conditioning module, data processing and storage module, RF transceiver, and power supply module. The sensors used, consist of temperature sensor LM35, pressure sensor ASDX-015A24R, and humidity sensor HS1101. The data processor uses Microcontroller ATMega128, while the RF transceiver module uses Chipcon CC1100 in 433 MHz Industrial, Scientific, Medical (ISM) Frequency. At the end of the research, the system development resulted in hardware which consists of four sensor nodes, 1 cluster head and 3 child nodes in a clustered topology, software in the form of TDMA-based MAC protocol, and system testing in a plant greenhouse. System performance has been tested through modular characterization, functionality testing, hardware and software testing, and field test, which showed good results. Hardware and software optimization based on energy efficiency have also been performed and the results show energy consumption conservation, based on load current calculation, up to 83% compared to the initial condition of the system.