Data Acquisition and Linearization of Sensors: Greenhouse Case Study

This work presents an overview of data acquisition, data logging and supervisory control of different parameters in a greenhouse. Raw measurement data from various parameters (surrounding temperature, pH of liquid, CO2 gas concentration) are acquired using DAQ and logged in a database for further analysis and supervisory control. For sensing the physical parameters, LM 35, pH probe, CO2 gas sensors are used. These sensors and DAQ needs uninterrupted power supply. For this purpose renewable energy is used to generate clean energy. Solar radiation can be used to generate electricity using PV (photo voltaic) cell and power conditioning circuit. This thesis is used to study the electrical characteristics of PV cell, which can be used to generate electricity from solar radiation for greenhouse purpose. Simulation studies have been carried out to know the electrical characteristics of PV cell for various irradiation levels. The sensors, which are mentioned above are mostly linear sensors. To use a nonlinear sensor suitably for data acquisition purpose, first of all the sensor linearization is done. In this work a thermistor is considered and its nonlinear characteristics are linearized using two methods (curve fitting method, Steinhart-Hart equation)

Distributed environmental monitoring

With increasingly ubiquitous use of web-based technologies in society today, autonomous sensor networks represent the future in large-scale information acquisition for applications ranging from environmental monitoring to in vivo sensing. This chapter presents a range of on-going projects with an emphasis on environmental sensing; relevant literature pertaining to sensor networks is reviewed, validated sensing applications are described and the contribution of high-resolution temporal data to better decision-making is discussed

Simulation of Greenhouse Climate Monitoring and Control with Wireless Sensor Network and Event-Based Control

Monitoring and control of the greenhouse environment play a decisive role in greenhouse production processes. Assurance of optimal climate conditions has a direct influence on crop growth performance, but it usually increases the required equipment cost. Traditionally, greenhouse installations have required a great effort to connect and distribute all the sensors and data acquisition systems. These installations need many data and power wires to be distributed along the greenhouses, making the system complex and expensive. For this reason, and others such as unavailability of distributed actuators, only individual sensors are usually located in a fixed point that is selected as representative of the overall greenhouse dynamics. On the other hand, the actuation system in greenhouses is usually composed by mechanical devices controlled by relays, being desirable to reduce the number of commutations of the control signals from security and economical point of views. Therefore, and in order to face these drawbacks, this paper describes how the greenhouse climate control can be represented as an event-based system in combination with wireless sensor networks, where low-frequency dynamics variables have to be controlled and control actions are mainly calculated against events produced by external disturbances. The proposed control system allows saving costs related with wear minimization and prolonging the actuator life, but keeping promising performance results. Analysis and conclusions are given by means of simulation results

Greenhouse microclimate real-time monitoring based on wireless sensor network and gis

Trabalho apresentado em XX IMEKO World Congress Metrology for Green Growth, 9-14 setembro de 2012, Busan, Coreia do SulThe usage of greenhouse with controlled microclimate represents an important way to increase the production of fruits and vegetables considering the plants needs and has recently become one of the hottest topics in precision agriculture. In order to know and to control the greenhouse microclimate smart sensing nodes with wireless communication capabilities represents the solution. As one of promissory protocol associated with wireless sensor network can be mentioned the ZigBee due to its low cost, low power consumption, extended ranges and architecture flexibility. In the present work a sensing and control sensing nodes with ZigBee communication capabilities are considered, while the microclimate is monitored using a set of solid state sensors for temperature, relative humidity, light intensity and CO2 concentration considering this parameters with important role in plants growing. Every sensor node uses energy from a solar cell through a battery charger circuit considering also the powering of the sensing and control node during the night periods. The data from ZigBee network nodes are sent to Wireless-Ethernet gateway connected to a computer that runs a LabVIEW application that perform primary processing and web geographic information system that provides information about the greenhouse microclimate. Elements related power harvesting for implemented wireless sensor network, as so as a set of experimental results are included in the present work.N/

Development of Greenhouse Monitoring using Wireless Sensor Network through ZigBee Technology

Greenhouses are often used for growing flowers, vegetables, fruits, and tobacco plants. Most greenhouse systems still use the manual system in monitoring the temperature and humidity in the greenhouse, a lot of problems can occur not for worker but also affected production rate because the temperature and humidity of the greenhouse must be constantly monitored to ensure optimal conditions. The Wireless Sensor Network (WSN) can be used to gather the data from point to point to trace down the local climate parameters in different parts of the big greenhouse to make the greenhouse automation system work properly. This paper presents the design of low cost greenhouse monitoring system to monitor a greenhouse temperature and humidity parameters by applying the ZigBee technology as the WSN system. During the design process, Peripheral Interface Controller (PIC), LCD Display and Zigbee as the main hardware components is used as hardware components while C compiler and MP Lab IDE were used for software elements. The data from the greenhouse was measured by the sensor then the data will be displayed on the LCD screen on the receiver which support up to 100 m range. By using this system, the process of monitoring is easier and it also cheaper for installation and maintenance. The feasibility of the developed node was tested by deploying a simple sensor network into the Agriculture Department of Melaka Tengah greenhouse in Malaysia

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

Environmental Application with Multi Sensor Network

This paper aimed to monitor temperature, humidity, and CO gas level using environmental application with multi sensor network (MSN). This system was applied in real life and real time, to be able to obtain data and information through mobile devices and other on internet network. In this research, environmental application is monitored remotely using displays on the web and sensors as device. This research obtained data in outdoor and indoor parking area also with obstacles and without obstacles, so it obtained the results from each of the different environmental conditions.   &nbsp

An Internet of Things Based Air Pollution Detection Device for Mitigating Climate Changes

Climate Change, a key stabilizing factor, has now exceeded critical thresholds. The high energy consumption of cities is a major contributor to climate change because of CO2 emissions. In addition to the rise in urban populations throughout the worldwide, the complexity of todays cities and the strain they put on limited resources means that the causes and consequences of climate changes become even more concentrated. Internet of Things (IoT) advancements provide several possibilities for reducing the effects of climate change by merging existing information, design techniques, and breakthrough technology. The current state of monitoring technology is subpar; it is insensitive, inaccurate, and requires laboratory examination. Consequently, new, and better methods of surveillance are required. Air pollution is one of the main causes of climate change. We suggest a new IoT-based monitoring device for air pollution to address the shortcoming of the current setup. Gas sensors, Arduino IDE, and Wi-Fi module were used to assemble the IoT kit. The air is analyzed by the gas sensors, and the results are sent to the Arduino software development environment. By using a WiFi module, the Arduino IDE may send data to the monitor. The resulting device may be deployed in different cities to monitor the levels of air pollution with little cost, easy to use and high accuracy

Decision support for optimised irrigation scheduling

The system, developed under the FLOW-AID (an FP6 project), is a farm level water management system of special value in situations where the water availability and quality is limited. This market-ready precision irrigation management system features new models, hardware and software. The hardware platform delivers a maintenance-free low cost dielectric tensiometer and several low-end irrigation or fertigation controllers for serving different situations. The software includes a complete, web based, Decision Support System (DSS) that consists of an expert planner for farm zoning (MOPECO) and a universal irrigation scheduler, based on crop-water stress models (UNIPI) and water and nutrient uptake calculations. The system, designed also to service greenhouse fertigation and hydroponics, is scalable from one to many zones. It consists of 1) a data gathering tool which uploads agronomic data, from monitored crops around the world, to a central web Data Base (DB), and 2) a web based Decision Support System (DSS). The DSS processes intelligently the data of the crop using Crop Response Models, Nutrient Uptake Models and Water Uptake Models. The central system returns over Internet to the low-end controller a command file containing water scheduling and nutrient supply guideline