Smart agriculture for optimizing photosynthesis using internet of things and fuzzy logic

Photosynthesis is a process that plants need. Plant growth requires sunlight to carry out photosynthesis. At night photosynthesis cannot be carried out by plants. This research proposes an internet of things (IoT) model that can work intelligently to maximize photosynthesis and plant growth using fuzzy logic. The plants used in this research are mustard plants because mustard plants are plants that have broad leaves and require more photosynthesis. The outputs of this proposed model are the activation of light emitting diodes (LED) lights and automatic watering based on input sensors such as soil moisture, temperature, and light intensity which are processed with fuzzy logic. The results show that the use of the IoT model that has been proposed can provide faster and better growth of mustard plants compared with mustard plants without an IoT system and fuzzy logic. This result is also strengthened by comparing the t-test between the two groups, with a significant 95% confidence level. The proposed model in this research is also compared with similar research models carried out previously. This research resulted in a plant height difference of 30.43% higher than the previous research. So, it can conclude that the proposed model can accelerate the growth of mustard plants

Dynamic safety assessment of a nonlinear pumped-storage generating system in a transient process

This paper focuses on a pumped-storage generating system with a reversible Francis turbine and presents an innovative framework for safety assessment in an attempt to overcome their limitations. Thus the aim is to analyze the dynamic safety process and risk probability of the above nonlinear generating system. This study is carried out based on an existing pumped-storage power station. In this paper we show the dynamic safety evaluation process and risk probability of the nonlinear generating system using Fisher discriminant method. A comparison analysis for the safety assessment is performed between two different closing laws, namely the separate mode only to include a guide vane and the linkage mode that includes a guide vane and a ball valve. We find that the most unfavorable condition of the generating system occurs in the final stage of the load rejection transient process. It is also demonstrated that there is no risk to the generating system with the linkage mode but the risk probability of the separate mode is 6 percent. The results obtained are in good agreement with the actual operation of hydropower stations. The developed framework may not only be adopted for the applications of the pumped-storage generating system with a reversible Francis turbine but serves as the basis for the safety assessment of various engineering applications.National Natural Science Foundation of ChinaFundamental Research Funds for the Central UniversitiesScientific research funds of Northwest A&F UniversityScience Fund for Excellent Young Scholars from Northwest A&F University and Shaanxi Nova progra

Optimal greenhouse cultivation control: survey and perspectives

Abstract: A survey is presented of the literature on greenhouse climate control, positioning the various solutions and paradigms in the framework of optimal control. A separation of timescales allows the separation of the economic optimal control problem of greenhouse cultivation into an off-line problem at the tactical level, and an on-line problem at the operational level. This paradigm is used to classify the literature into three categories: focus on operational control, focus on the tactical level, and truly integrated control. Integrated optimal control warrants the best economical result, and provides a systematic way to design control systems for the innovative greenhouses of the future. Research issues and perspectives are listed as well

Fuzzy system of irrigation applied to the growth of Habanero Pepper (Capsicum chinense Jacq.) under protected conditions in Yucatan, Mexico

Agriculture is the largest user of water worldwide by using about 70 percent of total consumption. The world food production depends on the availability of water, considering factors such as demographic and climate change, so the use of efficient irrigation is necessary to apply the correct amount of water to crops. The traditional irrigation systems generally program their scheme based on measurements made at Class A evaporimeter pan. In this paper an irrigation scheme defined by an algorithm that automates the amount of water supplied is presented, it considers the consumption of habanero pepper crop, and a fuzzy system evaluates the necessary duration of irrigation. The climatic variables considered are temperature, relative humidity, and soil moisture. The algorithm was programmed in a microcontroller Atmel 328p included in Arduino platform, with the addition of a ZigBee wireless system that allows for monitoring through a PC. The climatic variables were inserted into the fuzzy system by sets of trapezoidal and triangular form and a Mamdani type inference mechanism in which the knowledge of an expert is registered through the fuzzy rules. The system was applied to a habanero pepper crop at Conkal Institute of Technology in Yucatan, Mexico.Peer ReviewedPostprint (published version

Advancement of a smart fibrous capillary irrigation management system with an Internet of Things integration

This paper presents the development work for integrating an Internet of Things (IoT) with a fibrous capillary irrigation system based on the climatic demand estimated by the weather condition. The monitoring and control using an IoT system is critical for such application that is targeted for precision irrigation. The fibrous capillary irrigation system is managed by manipulating a water supply depth using the potential evapotranspiration (ETo). A soil mositure sensor was used to monitor the progress of the root water uptake and input the fuzzy logic system, to determine the water requirements for the crop medium. Experiment was conducted by using a Choy sum plant as the test crop grown in a greenhouse. The monitoring of the demand and management of the watering system was successful. The ETo data was able to approximate the crop water requirement in near real time