Smart greenhouses as the path towards precision agriculture in the food-energy and water nexus: case study of Qatar

Greenhouse farming is essential in increasing domestic crop production in countries with limited resources and a harsh climate like Qatar. Smart greenhouse development is even more important to overcome these limitations and achieve high levels of food security. While the main aim of greenhouses is to offer an appropriate environment for high-yield production while protecting crops from adverse climate conditions, smart greenhouses provide precise regulation and control of the microclimate variables by utilizing the latest control techniques, advanced metering and communication infrastructures, and smart management systems thus providing the optimal environment for crop development. However, due to the development of information technology, greenhouses are undergoing a big transformation. In fact, the new generation of greenhouses has gone from simple constructions to sophisticated factories that drive agricultural production at the minimum possible cost. The main objective of this paper is to present a comprehensive understanding framework of the actual greenhouse development in Qatar, so as to be able to support the transition to sustainable precision agriculture. Qatar’s greenhouse market is a dynamic sector, and it is expected to mark double-digit growth by 2025. Thus, this study may offer effective supporting information to decision and policy makers, professionals, and end-users in introducing new technologies and taking advantage of monitoring techniques, artificial intelligence, and communication infrastructure in the agriculture sector by adopting smart greenhouses, consequently enhancing the Food-Energy-Water Nexus resilience and sustainable development. Furthermore, an analysis of the actual agriculture situation in Qatar is provided by examining its potential development regarding the existing drivers and barriers. Finally, the study presents the policy measures already implemented in Qatar and analyses the future development of the local greenhouse sector in terms of sustainability and resource-saving perspective and its penetration into Qatar’s economy.Open Access funding provided by the Qatar National Library. The authors are grateful to Qatar National Research Fund (QNRF) for funding and supporting the M-NEX Project (Grant No. BFSUGI01-1120-170005) in Qatar. The M-NEX is a project of the Collaborative Research Area Belmont Forum (Grant No. 11314551)

Smart high-yield tomato cultivation: precision irrigation system using the Internet of Things

The Internet of Things (IOT)-based smart farming promises ultrafast speeds and near real-time response. Precision farming enabled by the Internet of Things has the potential to boost efficiency and output while reducing water use. Therefore, IoT devices can aid farmers in keeping track crop health and development while also automating a variety of tasks (such as moisture level prediction, irrigation system, crop development, and nutrient levels). The IoT-based autonomous irrigation technique makes exact use of farmers’ time, money, and power. High crop yields can be achieved through consistent monitoring and sensing of crops utilizing a variety of IoT sensors to inform farmers of optimal harvest times. In this paper, a smart framework for growing tomatoes is developed, with influence from IoT devices or modules. With the help of IoT modules, we can forecast soil moisture levels and fine-tune the watering schedule. To further aid farmers, a smartphone app is currently in development that will provide them with crucial data on the health of their tomato crops. Large-scale experiments validate the proposed model’s ability to intelligently monitor the irrigation system, which contributes to higher tomato yields

An algorithm to schedule water delivery in pressurized irrigation networks

This study presents a deterministic constrained optimisation algorithm developed for using in a pressurized irrigation network. In irrigation networks —or water networks supplied by a head tank— utility managers can fully adapt the delivery times to suit their needs. The program provides a strategy for scheduling water delivery at a constant flow rate (opening and closing of hydrants, units, and subunits) to minimise energy consumption. This technique improves on earlier approaches by employing a deterministic method with little computing time. This method has been tested in the University of Alicante pressurized irrigation network, where decision-makers have identified the need to diminish the energy expenditure for watering University’s gardens.This work was supported by the research project “DESENREDA” through the 2021 call “Estancias de movilidad en el extranjero Jose Castillejo” of the Ministerio de Universidades (CAS21/00085) and for the project “Hi-Edu Carbon” Erasmus Plus Programme, Key Action KA22021, action type (2021-1-SK01-KA220-HED-000023274

Hierarchical model predictive control of a venlo-type greenhouse

Greenhouse cultivation can increase crop yield and alleviate the food shortage caused by population growth and reduction of arable land. However, the greenhouse production process consumes lots of energy and water. The energy consumed mainly comes from the combustion of fossil fuels, which will produce lots of greenhouse gases. In addition, the operating efficiency of some greenhouses is low, resulting in energy and water waste and increasing production costs. Therefore, the greenhouse system needs to be optimized to improve the operating efficiency. In this thesis, different methods of greenhouse operation efficiency optimization to improve energy efficiency and water efficiency are studied. In Chapter 3, three strategies for greenhouse operation optimization are studied. Strategy 1 focuses on the optimization of the greenhouse heating system to save energy. The optimization of the heating system can effectively reduce energy consumption. However, people often pay more attention to reducing energy costs than reducing energy consumption in the production process to obtain more profits. Strategy 2 is to reduce the energy cost. It should be noted that Strategy 2 only considers the cost of heating and cooling, while the cost of ventilation and carbon dioxide (CO2) is not considered. Strategy 3 reduces the cost of greenhouse heating, cooling, ventilation and CO2 consumption. In addition, greenhouse environmental factors must be kept within the required ranges. In Chapter 3, a dynamic greenhouse climate model is proposed. In the modeling process, the influence of crop growth and the interaction between different variables are considered to improve model accuracy. The proposed optimization problems are solved by ‘fmincon’ function with sequential quadratic programming (SQP) algorithm in MATLAB. Compared with Strategy 1, Strategy 2 has higher energy consumption but lower energy cost. Because Strategy 2 can shift some loads from high electricity price period to low electricity price period. Moreover, among the three strategies proposed, Strategy 3 has the lowest cost. It should be pointed out that the strategies studied in Chapter 3 only consider the impact of the greenhouse climate, but ignore the irrigation, which is also important for greenhouse production. In Chapter 4, four optimization methods are proposed. These optimization methods consider climate control and irrigation control. Therefore, strategies proposed in this chapter can not only improve energy efficiency, but also increase water efficiency. Method 1 reduces the energy consumption. Method 2 reduces the water consumption. Method 3 reduces the CO2 consumption. Method 4 reduces the total cost of greenhouse heating, cooling, ventilation, irrigation and CO2 supply. In addition, greenhouse environmental factors and crop water demand need to be met. The dynamic model of greenhouse environmental factors presented in Chapter 3 is used for greenhouse climate control. A modified crop evapotranspiration model is proposed to predict crop water demand. Moreover, a sensitivity analysis method is introduced. The influence of prices and system constraints on optimization results is studied. The cost of Method 4 can be reduced compared with other methods. In addition, changes of prices and system constraints have a great impact on optimization results. In Chapters 3 and 4, open loop optimization strategies for a greenhouse system operation are studied. However, these strategies have low control accuracy under system disturbances. Therefore, it is necessary to adopt some control methods to improve the control accuracy. In Chapter 5, a hierarchical model predictive control method is presented. The upper layer generates the optimal reference trajectories by solving greenhouse operation optimization problems. The lower layer designs controllers to follow obtained reference trajectories. Two model predictive controllers (MPC) are designed. Two performance indicators, namely relative average deviation (RAD) and maximum relative deviation (MRD), are used to compare designed controllers. The simulation results show that the proposed MPC can deal with greenhouse system disturbances and the problem of model plant mismatch better than the open loop control method. In Chapter 6, the findings of this thesis are summarized. Moreover, some topics for future research are proposed.Thesis (PhD (Electrical Engineering))--University of Pretoria, 2021.Electrical, Electronic and Computer EngineeringPhD (Electrical Engineering)Unrestricte

Sector-Based Water Demand Forecasting: Commercial Greenhouses

With rising electricity prices, forecasting water demand has become an essential part of the success of any water utility. Numerous forecasting methods have been suggested, but none have been able to characterize the unique consumer mixes that exist for every utility. This work focuses on a water utility located in Essex County, Ontario, Canada. Examination of the utilities consumer breakdown showed that almost 80% of their capacity was being consumed by commercial greenhouse operations. Current forecasting practices in this region for this sector are almost non-existent, assuming fixed demand for all greenhouse operations. This study presents three papers that focus on evaluation and simplification of forecasting techniques for commercial greenhouse operations. The first paper examines influential factors which drive greenhouse water consumption, with an emphasis on practicality. The second paper evaluates several forecasting model architectures ranging from elementary to complex in order to determine the most suitable method(s). The third paper compares water usage between two crops (tomatoes and bell peppers) in an effort to evaluate a crop to crop forecast technique that relies on one crops watering data in order to produce forecasts for another crop

Smart greenhouse and plant growth control

Since the development of agriculture is an important problem for every state, huge funds are allocated to this industry. However, the problem of lack of fresh fruits/vegetables, that is, the problem of import substitution remains a pressing issue in many countries. The aim of the study was to inspect the growth of plants in a home-based mini-greenhouse, for which reason the following tasks were set: conduct a biological experiment; search for dependence of the influence of environmental conditions (microclimate) on growth. The paper highlights the problem of import substitution of vegetables in Kazakhstan, and suggests the best way to solve this issue. The proposed solution offers the development of mini-greenhouse that meets the criteria of price and quality. The developed system differs from other smart greenhouses, firstly, by its availability to a wide range of users (price criterion), and secondly, by ensuring agrotechnical, energy, and design requirements (quality criterion). These requirements are implemented through the use of promising technologies: phytomonitoring, intelligent technologies and open source software, the use of available construction materials and water saving technologies such as drip irrigation. The economic effect from the use of the proposed technology has amounted to 10,000 tenge, the payback period was 4 seasons

Sizing and energy management for Photovoltaic Pumping

En las últimas décadas, la energía fotovoltaica se ha convertido en una fuente eficaz de energía para la producción de la electricidad, que se utilizará en sitios aislados o será inyecta en la red. En zonas aisladas, las instalaciones fotovoltaicas se han utilizado para el bombeo de agua para la agricultura o para fines humanos, debido a su facilidad de instalar y su bajo coste de mantenimiento después de la instalación. Sin embargo, la variabilidad inherente exige elegir cuidadosamente el tamaño de la instalación y proporcionar un algoritmo de gestión de la energía. Por lo tanto, esta tesis se centra en el cálculo del tamaño y la gestión energética de una instalación fotovoltaica autónoma destinada al bombeo de agua para irrigación en un lugar aislado. Normalmente, este tipo de instalaciones se utiliza ampliamente en las regiones áridas y semi-áridas como el Magreb y el Sur de Europa, donde existe una importante disponibilidad de radiación solar. Se requiere el funcionamiento correcto de estas plantas para satisfacer la demanda de agua, optimizar el uso de la energía fotovoltaica y para extender el tiempo de vida de los componentes. Estos objetivos pueden asegurarse por un buen dimensionamiento de los componentes y una gestión óptima de la energía, que representan las dos partes principales de la tesis. De hecho, la primera parte de esta tesis trata del dimensionamiento de los componentes de la instalación de riego fotovoltaico, es decir, los paneles fotovoltaicos y el banco de baterías. Por lo tanto, un algoritmo para el dimensionamiento óptimo de los componentes de la instalación se ha establecido, con base en las necesidades de agua de los cultivos, las características climáticas del sitio y las restricciones de los componentes. Para esto, fue necesario seleccionar algunos modelos de los componentes de la instalación, que han sido validados experimentalmente. Además, se han estudiado algunas técnicas relacionadas con la extracción máxima de energía fotovoltaica. Entonces, el algoritmo de dimensionamiento ha sido validado con datos medidos de la zona objetivo (Medjez El Beb, al norte de Túnez).Departamento de Ingeniería de Sistemas y Proceso

Green Technologies for Production Processes

This book focuses on original research works about Green Technologies for Production Processes, including discrete production processes and process production processes, from various aspects that tackle product, process, and system issues in production. The aim is to report the state-of-the-art on relevant research topics and highlight the barriers, challenges, and opportunities we are facing. This book includes 22 research papers and involves energy-saving and waste reduction in production processes, design and manufacturing of green products, low carbon manufacturing and remanufacturing, management and policy for sustainable production, technologies of mitigating CO2 emissions, and other green technologies

The modern water-saving agricultural technology: Progress and focus

Based on the analysis of water-saving agricultural technology development status and trends in China, and in combination with the development and the needs of modern water-saving agricultural technology, we have put forward a future research emphasis and developing direction of modern watersaving agricultural technology, which include modern biological water-saving technology, unconventional high-efficient and safe-water using technology, water-saving irrigation technology and equipment, dry high-efficient water using technology and new materials regional high-efficient watersaving agriculture comprehensive technology.Key words: Biological water-saving technology, unconventional water resource, water-saving irrigation, dry-land water high-efficient agriculture, technical integration, biotechnology