An Optimization Scheme Based on Fuzzy Logic Control for Efficient Energy Consumption in Hydroponics Environment

As the world population is increasing rapidly, food and water demands are the most crucial problem for humanity. In some areas of the world, water or environment is unsuitable for plant growth; hydroponic systems can provide a suitable environment for crop production with effective management of natural resources. Internet of Things paradigm based automated systems has been creating an excellent opportunity for monitoring and controlling agriculture by minimizing the cost and maximizing the profit significantly over the past decade. The reduction of the cost can be achieved by sufficient usage of resources and setting up optimum operational parameters for agricultural devices. This paper presents an optimization scheme with novel objective function for hydroponics environment parameters management with efficient energy consumption. The proposed approach provides optimal energy and resource utilization in the hydroponics system with setting up a working level and operational duration to the actuators. We have developed an optimization scheme with objective function for optimal humidity and water level control based on fuzzy logic, which can support the optimal measurement for crop growth with energy efficiency. Fuzzy logic control is applied for the compromise between actuators working level and operational duration. A real hydroponics environment has been implemented and presented to evaluate the effectiveness of the proposed approach. It can be assessed through the simulation results that the optimization module achieves a signification reduction (18%) in energy consumption as compared to the other scheme.

[1]  Do-Hyeun Kim,et al.  A Novel Approach towards Resource Auto-Registration and Discovery of Embedded Systems Based on DNS , 2019 .

[2]  Marimuthu Palaniswami,et al.  Internet of Things (IoT): A vision, architectural elements, and future directions , 2012, Future Gener. Comput. Syst..

[3]  Faisal Mehmood,et al.  Object detection mechanism based on deep learning algorithm using embedded IoT devices for smart home appliances control in CoT , 2019, Journal of Ambient Intelligence and Humanized Computing.

[4]  Fernanda Ludwig,et al.  Electrical conductivity and pH of the substrate solution in gerbera cultivars under fertigation , 2013 .

[5]  Louis D. Albright,et al.  PREDICTIVE NEURAL NETWORK MODELING OF pH AND ELECTRICAL CONDUCTIVITY IN DEEP–TROUGH HYDROPONICS , 2002 .

[6]  Q. Shen,et al.  Understanding Water-Stress Responses in Soybean Using Hydroponics System—A Systems Biology Perspective , 2015, Front. Plant Sci..

[7]  Wenquan Jin,et al.  Consistent Registration and Discovery Scheme for Devices and Web Service Providers Based on RAML Using Embedded RD in OCF IoT Network , 2018, Sustainability.

[8]  Faisal Mehmood,et al.  Design and Development of a Real-Time Optimal Route Recommendation System Using Big Data for Tourists in Jeju Island , 2019, Electronics.

[9]  Kaushal Kumar,et al.  Hydroponics as an advanced technique for vegetable production: An overview , 2018 .

[10]  Imran Ali Lakhiar,et al.  Monitoring and Control Systems in Agriculture Using Intelligent Sensor Techniques: A Review of the Aeroponic System , 2018, J. Sensors.

[11]  Rijo Jackson Tom,et al.  IoT based hydroponics system using Deep Neural Networks , 2018, Comput. Electron. Agric..

[12]  Patcharin Songsri,et al.  Hydroponics: An Alternative Method for Root and Shoot Classification on Sugarcane Genotypes , 2019, AGRIVITA Journal of Agricultural Science.

[13]  H.-J. Zimmermann Fuzzy set theory , 2010 .

[14]  Lotfi A. Zadeh,et al.  Fuzzy logic - a personal perspective , 2015, Fuzzy Sets Syst..

[15]  N. Fedoroff,et al.  Hollow fibre membrane-based liquid desiccant humidity control for controlled environment agriculture , 2019, Biosystems Engineering.