| dc.description.abstract | Increasing crop yields is essential in the agricultural sector to fulfill the
intensifying population's fast rising food demand. Automation is the only way to
improve industrial production. Manual methods must give way to automation
immediately. One of the many crops that we cannot overlook when talking about
agriculture is the chile. A staple of everyday cooking, chili is a highly valuable
vegetable. The inefficiency of air temperature, irrigation, and soil moisture levels
monitoring and regulation is one of the primary problems in the production of
chilies. The solution can be found through the use of IoT, which enables real-time
data collection and the use of fuzzy logic methods for more adaptive and automatic
decision-making in managing the plant environment. Technologies like IoT are
used to bring a new revolution in agricultural methods. This system uses a fuzzy
logic algorithm approach to calculate plant conditions and the amount of water to
be irrigated. Fuzzy logic is a reasoning method based on approaches and
assumptions that resemble human reasoning models. Currently, this algorithm is
widely used in fields such as robotics, automated production lines, financial
simulations, and others. For the design stage, the Sugeno method is used in fuzzy
logic. Sugeno is also known as the Fuzzy Inference System (FIS). It is one method
of drawing conclusions in a system that uses fuzzy logic. "IF-THEN" is the
representation of the rule base in this fuzzy system. Applications where the output
results must be integrated with other mathematical or analytical models are
appropriate for this approach. Based on information gathered from sensors on soil
moisture content and ambient temperature, the system controls how much water is
given to the plants. The output obtained from the devices has shown good
performance, especially in collecting, displaying, and analyzing data. | en_US |
