Intelligent Greenhouse Monitoring and Control System Based Arduino UNO Microcontroller

Nowadays, there is a significant diminution in agricultural production due to the unpredictable control of crop climate conditions. Thus, to alleviate the crops exposure from excess cold or heat and unwanted pests, an intelligent environment monitoring and control system based Arduino UNO board consisting of ATmega 328P microcontroller has been developed for a small-scale agriculture namely greenhouse. The system user can monitor and control the greenhouse climate conditions remotely via web interface/mobile applications and GSM in a real-time manner. To deliver the environmental conditions in a timely manner, low-cost wireless sensor network (WSN) is used to monitor the temperature, humidity, soil moisture and light of the greenhouse. The sensor network constitutes a multi-hop network structure for large coverage. The developed system is implemented and tested in laboratory conditions using Proteus toolkit. Arduino Integrated Development Environment (IDE) tool is used to develop necessary software. The results show that the proposed system can closely monitor and evaluate greenhouse farming field conditions accurately. Finally, the user can send control decisions instantly to boost the yield growth conditions and thus, increase the crop production considerably

Research Trends on Greenhouse Engineering Using a Science Mapping Approach

Horticultural protected cultivation has spread throughout the world as it has proven to be extremely effective. In recent years, the greenhouse engineering research field has become one of the main research topics within greenhouse farming. The main objectives of the current study were to identify the major research topics and their trends during the last four decades by analyzing the co-occurrence network of keywords associated with greenhouse engineering publications. A total of 3804 pertinent documents published, in 1981-2021, were analyzed and discussed. China, the United States, Spain, Italy and the Netherlands have been the most active countries with more than 36% of the relevant literature. The keyword cluster analysis suggested the presence of five principal research topics: energy management and storage; monitoring and control of greenhouse climate parameters; automation of greenhouse operations through the internet of things (IoT) and wireless sensor network (WSN) applications; greenhouse covering materials and microclimate optimization in relation to plant growth; structural and functional design for improving greenhouse stability, ventilation and microclimate. Recent research trends are focused on real-time monitoring and automatic control systems based on the IoT and WSN technologies, multi-objective optimization approaches for greenhouse climate control, efficient artificial lighting and sustainable greenhouse crop cultivation using renewable energy

Система моніторингу параметрів навколишнього середовища промислового об’єкту

Об’єкт дослідження є безпроводова мережа на основі технології ZigBee для управління інженерними системами промислового тепличного комплексу. Метою роботи є розробка топології та структурної схеми безпроводової мережі, вибір компонентів для неї, розробка функціональної, принципової схеми модуля контролю мікроклімату теплиці для даної мережі. Методом дослідження є теоретичне дослідження можливості побудови безпроводової мережі на основі технології ZigBee для використання в системах сигналізації, управління освітленням, кліматом тощо. В результаті виконання магістерської дисертації були розроблені структурна схема та топологія мережі, функціональна та принципова схеми модуля для контролю клімату теплиці. Галузь застосування: мережа може використовуватись при створенні систем автоматизованих тепличних комплексів, безпроводових систем сигналізації, сенсорних мереж.The research object is a wireless network based on ZigBee technology for managing the engineering systems of the industrial greenhouse complex. The purpose of the work is developing the topology and structural scheme of the wireless network, the choice of components for it, the development of a functional, principal scheme of the climate control module for greenhouses for the network. The research method is a theoretical study of the possibility of building a wireless network based on ZigBee technology for use in alarm systems, lighting control, climate, etc. As a result of the master's dissertation, a structural scheme and network topology, a functional and principal scheme of the module for climate control of the greenhouse were developed. Area of application: the network can be used for creating systems of automated greenhouse complexes, wireless signaling systems, sensor networks

Root Zone Sensors for Irrigation Management in Intensive Agriculture

Crop irrigation uses more than 70% of the world’s water, and thus, improving irrigation efficiency is decisive to sustain the food demand from a fast-growing world population. This objective may be accomplished by cultivating more water-efficient crop species and/or through the application of efficient irrigation systems, which includes the implementation of a suitable method for precise scheduling. At the farm level, irrigation is generally scheduled based on the grower’s experience or on the determination of soil water balance (weather-based method). An alternative approach entails the measurement of soil water status. Expensive and sophisticated root zone sensors (RZS), such as neutron probes, are available for the use of soil and plant scientists, while cheap and practical devices are needed for irrigation management in commercial crops. The paper illustrates the main features of RZS’ (for both soil moisture and salinity) marketed for the irrigation industry and discusses how such sensors may be integrated in a wireless network for computer-controlled irrigation and used for innovative irrigation strategies, such as deficit or dual-water irrigation. The paper also consider the main results of recent or current research works conducted by the authors in Tuscany (Italy) on the irrigation management of container-grown ornamental plants, which is an important agricultural sector in Italy

Smart System for Bicarbonate Control in Irrigation for Hydroponic Precision Farming

[EN] Improving the sustainability in agriculture is nowadays an important challenge. The automation of irrigation processes via low-cost sensors can to spread technological advances in a sector very influenced by economical costs. This article presents an auto-calibrated pH sensor able to detect and adjust the imbalances in the pH levels of the nutrient solution used in hydroponic agriculture. The sensor is composed by a pH probe and a set of micropumps that sequentially pour the different liquid solutions to maintain the sensor calibration and the water samples from the channels that contain the nutrient solution. To implement our architecture, we use an auto-calibrated pH sensor connected to a wireless node. Several nodes compose our wireless sensor networks (WSN) to control our greenhouse. The sensors periodically measure the pH level of each hydroponic support and send the information to a data base (DB) which stores and analyzes the data to warn farmers about the measures. The data can then be accessed through a user-friendly, web-based interface that can be accessed through the Internet by using desktop or mobile devices. This paper also shows the design and test bench for both the auto-calibrated pH sensor and the wireless network to check their correct operation.The research leading to these results has received funding from "la Caixa" Foundation and Triptolemos Foundation. This work has also been partially supported by European Union through the ERANETMED (Euromediterranean Cooperation through ERANET joint activities and beyond) project ERANETMED3-227 SMARTWATIRCambra-Baseca, C.; Sendra, S.; Lloret, J.; Lacuesta, R. (2018). Smart System for Bicarbonate Control in Irrigation for Hydroponic Precision Farming. Sensors. 18(5):1-16. https://doi.org/10.3390/s18051333S116185Salley, S. W., Sleezer, R. O., Bergstrom, R. M., Martin, P. H., & Kelly, E. F. (2016). A long-term analysis of the historical dry boundary for the Great Plains of North America: Implications of climatic variability and climatic change on temporal and spatial patterns in soil moisture. Geoderma, 274, 104-113. doi:10.1016/j.geoderma.2016.03.020Yang, H., Du, T., Qiu, R., Chen, J., Wang, F., Li, Y., … Kang, S. (2017). Improved water use efficiency and fruit quality of greenhouse crops under regulated deficit irrigation in northwest China. Agricultural Water Management, 179, 193-204. doi:10.1016/j.agwat.2016.05.029Ferentinos, K. P., Katsoulas, N., Tzounis, A., Bartzanas, T., & Kittas, C. (2017). Wireless sensor networks for greenhouse climate and plant condition assessment. Biosystems Engineering, 153, 70-81. doi:10.1016/j.biosystemseng.2016.11.005Ibayashi, H., Kaneda, Y., Imahara, J., Oishi, N., Kuroda, M., & Mineno, H. (2016). A Reliable Wireless Control System for Tomato Hydroponics. Sensors, 16(5), 644. doi:10.3390/s16050644Ntinas, G. K., Neumair, M., Tsadilas, C. D., & Meyer, J. (2017). Carbon footprint and cumulative energy demand of greenhouse and open-field tomato cultivation systems under Southern and Central European climatic conditions. Journal of Cleaner Production, 142, 3617-3626. doi:10.1016/j.jclepro.2016.10.106Europapress Newshttp://www.europapress.es/andalucia/almeria-00350/noticia-superficie-invernaderos-crece-105-ultimos-cuatro-anos-llegar-29596-hectareas-20150213102204.htmlTreftz, C., & Omaye, S. T. (2016). Hydroponics: potential for augmenting sustainable food production in non-arable regions. Nutrition & Food Science, 46(5), 672-684. doi:10.1108/nfs-10-2015-0118De Anda, J., & Shear, H. (2017). Potential of Vertical Hydroponic Agriculture in Mexico. Sustainability, 9(1), 140. doi:10.3390/su9010140Croft, M. M., Hallett, S. G., & Marshall, M. I. (2017). Hydroponic production of vegetable Amaranth (Amaranthus cruentus) for improving nutritional security and economic viability in Kenya. Renewable Agriculture and Food Systems, 32(6), 552-561. doi:10.1017/s1742170516000478Ferrarezi, R. S., & Testezlaf, R. (2014). Performance of wick irrigation system using self-compensating troughs with substrates for lettuce production. Journal of Plant Nutrition, 39(1), 147-161. doi:10.1080/01904167.2014.983127Understanding Irrigation Water Test Results and Their Implications on Nursery and Greenhouse Crophttps://uknowledge.uky.edu/cgi/viewcontent.cgi?article=1160&context=anr_reportsKim, H.-J., Kim, D.-W., Kim, W. K., Cho, W.-J., & Kang, C. I. (2017). PVC membrane-based portable ion analyzer for hydroponic and water monitoring. Computers and Electronics in Agriculture, 140, 374-385. doi:10.1016/j.compag.2017.06.015(2017). Remote Sensing for Irrigation of Horticultural Crops. Horticulturae, 3(2), 40. doi:10.3390/horticulturae3020040Suárez-Albela, M., Fraga-Lamas, P., Fernández-Caramés, T., Dapena, A., & González-López, M. (2016). Home Automation System Based on Intelligent Transducer Enablers. Sensors, 16(10), 1595. doi:10.3390/s16101595Zhang, Q., Yang, X., Zhou, Y., Wang, L., & Guo, X. (2007). A wireless solution for greenhouse monitoring and control system based on ZigBee technology. Journal of Zhejiang University-SCIENCE A, 8(10), 1584-1587. doi:10.1631/jzus.2007.a1584Gill, S. S., Chana, I., & Buyya, R. (2017). IoT Based Agriculture as a Cloud and Big Data Service. Journal of Organizational and End User Computing, 29(4), 1-23. doi:10.4018/joeuc.2017100101Nordic Semiconductor, RF Specialist in Ultra-Low Power Wireless Communicationshttp://www.nordicsemi.com/eng/Products/2.4GHzRF/nRF24L01Pawlowski, A., Guzman, J., Rodríguez, F., Berenguel, M., Sánchez, J., & Dormido, S. (2009). Simulation of Greenhouse Climate Monitoring and Control with Wireless Sensor Network and Event-Based Control. Sensors, 9(1), 232-252. doi:10.3390/s90100232Li, X., Cheng, X., Yan, K., & Gong, P. (2010). A Monitoring System for Vegetable Greenhouses based on a Wireless Sensor Network. Sensors, 10(10), 8963-8980. doi:10.3390/s10100896

Farm level optimal water management: Assistant for irrigation under Defecit (FLOW-AID)

Flow-aid is an on-going 6th Framework European project (2006-2009) with the objective to contribute to sustainable irrigated agriculture by developing an irrigation management system that can be used for crop production in cases with limited water supply and marginal water quality. The project integrates innovative sensor technologies into a decision support system, taking into consideration boundary conditions and constraints for a number of practical growing systems in the Mediterranean. It focuses on innovative, simple and affordable, hard- and software concepts for deficit irrigation; particularly a maintenance free tensiometer, a wireless and low-power sensor network; an expert system to assist annual farm zoning and crop planning in view of expected water availability and quality; and an irrigation scheduler for allocation of water for multiple plots at farm level. The system is being evaluated at four sites located in Italy, Turkey, Lebanon and Jordan. The sites are chosen in such a way that they differ in the type of constraints, irrigation structures, crop types, water supplies (availability of amount and quality), the local goals, and their complexity. This paper describes the overall concept and briefly the progress of the first year research

Greenhouse Monitoring with Wireless Sensor Network

Financially profitable greenhouses are fully automated. The producer defines the monitoring limits for the ideal growth environment and then, the system controls automatically each adjustment to keep indoor climate at the optimal level. Increasing greenhouse sizes have forced the producers to use several measurement points for tracking the changes in the environment, thus enabling energy saving and more accurate adjustments. When each measurement point needs its own wire, the costs and cabling work increase exponentially. Once the measurement spot has been built, it is tedious to be relocated. Wireless sensor networks are gained ground in various industries. Agriculture and especially microclimate monitoring and controlling have many promising targets where the benefits of wireless devices can be exploited. In this M.Sc. thesis we discuss the wireless sensor networks applications for greenhouses monitoring. Moreover, we have built the system practically and assist the applicability of such wireless networks through real-side measurements. Star topology network measured temperature, humidity and irradiance –important developmental factors of the plants in Martens greenhouse research foundation. Test setup greenhouse was divided into vertical blocks and nodes monitor one block at a time. The idea of the vertical distribution was to gather information about the differences occurs in the climate between lower and upper flora. The measurement results proved the functionality and reliability of the wireless sensor network inside the dense and high moisture greenhouse.fi=Opinnäytetyö kokotekstinä PDF-muodossa.|en=Thesis fulltext in PDF format.|sv=Lärdomsprov tillgängligt som fulltext i PDF-format

Simulation of site-specific irrigation control strategies with sparse input data

Crop and irrigation water use efficiencies may be improved by managing irrigation application timing and volumes using physical and agronomic principles. However, the crop water requirement may be spatially variable due to different soil properties and genetic variations in the crop across the field. Adaptive control strategies can be used to locally control water applications in response to in-field temporal and spatial variability with the aim of maximising both crop development and water use efficiency. A simulation framework ‘VARIwise’ has been created to aid the development, evaluation and management of spatially and temporally varied adaptive irrigation control strategies (McCarthy et al., 2010). VARIwise enables alternative control strategies to be simulated with different crop and environmental conditions and at a range of spatial resolutions. An iterative learning controller and model predictive controller have been implemented in VARIwise to improve the irrigation of cotton. The iterative learning control strategy involves using the soil moisture response to the previous irrigation volume to adjust the applied irrigation volume applied at the next irrigation event. For field implementation this controller has low data requirements as only soil moisture data is required after each irrigation event. In contrast, a model predictive controller has high data requirements as measured soil and plant data are required at a high spatial resolution in a field implementation. Model predictive control involves using a calibrated model to determine the irrigation application and/or timing which results in the highest predicted yield or water use efficiency. The implementation of these strategies is described and a case study is presented to demonstrate the operation of the strategies with various levels of data availability. It is concluded that in situations of sparse data, the iterative learning controller performs significantly better than a model predictive controller