Development of Fuzzy-Based Smart Drip Irrigation System for Chili Cultivation

Abstract

Chili plants often fail to harvest in the cultivation process due to improper irrigation. Soil temperature and humidity are essential parameters that affect the amount of water needed by plants in the watering process. This research aimed to apply fuzzy logic to the chili plants' irrigation system. The function of this system was to regulate watering due to the needs of the Chili plant automatically in a real-time fashion. The Sugeno fuzzy inference system (FIS) is embedded in a microcontroller to regulate the water based on the plant's needs appropriately. The system was tested on Chili plants located in the iSurf Computer Science Lab IPB University greenhouse. After four days of testing, the soil moisture sensor results were stable at optimal conditions, between 60%-80% after watering. It shows that the irrigation system has automatically regulated watering due to the Chili plant's needs.

A Smart Greenhouse Production System Utilizes an IoT Technology

“…Lastly, in earlier studies, some researches end with an action as an answer by the system to the environment such as adjusting the valve or turning on the water pump [21]- [23]. However, in this study, the proposed system provides a further response.…”

“…The IoT devices consist of Arduino Uno R3, Soil Moisture Sensor, Liquid Crystal Display (LCD) 16x2 with I2C Converter, 12V Water Pump, Relay DC 12V, Resistor, Transistor BC548, and AC to DC Converter connected to the power supply. All those things are the minimum specifications of IoT Concepts implemented in agriculture field [21], [22].…”

“…Blackbox Testing is one of testing method to measure system functionality based on suitability in completing task of requirements. The proposed system is tested in 3-4 days based on the previous research [21].…”

Digital Twin Platform Architecture Design to Support Smart Aeroponic Potato Cultivation in Indonesia

“…2) at IPB University, Bogor, Indonesia, which provides a controlled space and wireless sensor networks underlying infrastructure. The lab previously has been used in other research such as [11] and [14].…”

“…The architecture design consists of the in-farm sensor networks, a back-end database system, and a DT module to visualize the cultivated potato's actual condition based on sensor data. The produced architecture design will serve as our next experiment to build both the physical and virtual system of potato digital twins in the Internet of Things for Smart Urban Farming Laboratory (I-Surf Lab) at IPB University [11].…”