A Wireless Sensor Network-Based Ubiquitous Paprika Growth Management System

Wireless Sensor Network (WSN) technology can facilitate advances in productivity, safety and human quality of life through its applications in various industries. In particular, the application of WSN technology to the agricultural area, which is labor-intensive compared to other industries, and in addition is typically lacking in IT technology applications, adds value and can increase the agricultural productivity. This study attempts to establish a ubiquitous agricultural environment and improve the productivity of farms that grow paprika by suggesting a ‘Ubiquitous Paprika Greenhouse Management System’ using WSN technology. The proposed system can collect and monitor information related to the growth environment of crops outside and inside paprika greenhouses by installing WSN sensors and monitoring images captured by CCTV cameras. In addition, the system provides a paprika greenhouse environment control facility for manual and automatic control from a distance, improves the convenience and productivity of users, and facilitates an optimized environment to grow paprika based on the growth environment data acquired by operating the system

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

Security and Privacy for Green IoT-based Agriculture: Review, Blockchain solutions, and Challenges

open access articleThis paper presents research challenges on security and privacy issues in the field of green IoT-based agriculture. We start by describing a four-tier green IoT-based agriculture architecture and summarizing the existing surveys that deal with smart agriculture. Then, we provide a classification of threat models against green IoT-based agriculture into five categories, including, attacks against privacy, authentication, confidentiality, availability, and integrity properties. Moreover, we provide a taxonomy and a side-by-side comparison of the state-of-the-art methods toward secure and privacy-preserving technologies for IoT applications and how they will be adapted for green IoT-based agriculture. In addition, we analyze the privacy-oriented blockchain-based solutions as well as consensus algorithms for IoT applications and how they will be adapted for green IoT-based agriculture. Based on the current survey, we highlight open research challenges and discuss possible future research directions in the security and privacy of green IoT-based agriculture

Implementasi Wireless Sensor Network Untuk Otomatisasi Suhu Ruang Dan Kelembaban Tanah Pada Greenhouse Berbasis Web Server

Along with the increasing population of Indonesia which is also followed by the increasing rate of urbanization in the industrial sector, certainly affects the reduced agricultural sector to increase food needs. Greenhouse can be one solution to solve this problem, by utilize greenhouse our enviroment can be controlled and also protect the plants from outside interference. During this condition is still done manually both to measure the temperature or watering the plants. In this study the author developed a system to monitor and automate room temperature and soil moisture in greenhouse by utilizing Wireless Sensor Network (WSN) technology. The system consists of 1 node temperature and humidity chamber and 1 node of greenhouse soil moisture where each node is composed of arduino uno as its microcontroller, ESP8266 as Wi-Fi module, sensor, and relay. The results of monitoring and automation data will be sent to the web server by wireless, to make it easier for greenhouse farmers and monitoring their greenhouse. The results of this study can be found that the system is able to monitor and perform automatic control of temperature decrease, when the temperature reaches more than 28C and able to increase soil moisture automatically when the soil moisture is less than 40%, in addition by using ESP8266 data monitoring and automation results can be sent to the web server but based on the test results obtained that the maximum range of data transmission is 50 meters from the node to the access point

Wireless Sensor Network-Based Greenhouse Environment Monitoring and Automatic Control System for Dew Condensation Prevention

Dew condensation on the leaf surface of greenhouse crops can promote diseases caused by fungus and bacteria, affecting the growth of the crops. In this paper, we present a WSN (Wireless Sensor Network)-based automatic monitoring system to prevent dew condensation in a greenhouse environment. The system is composed of sensor nodes for collecting data, base nodes for processing collected data, relay nodes for driving devices for adjusting the environment inside greenhouse and an environment server for data storage and processing. Using the Barenbrug formula for calculating the dew point on the leaves, this system is realized to prevent dew condensation phenomena on the crop’s surface acting as an important element for prevention of diseases infections. We also constructed a physical model resembling the typical greenhouse in order to verify the performance of our system with regard to dew condensation control

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

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

Air pollution and livestock production

The air in a livestock farming environment contains high concentrations of dust particles and gaseous pollutants. The total inhalable dust can enter the nose and mouth during normal breathing and the thoracic dust can reach into the lungs. However, it is the respirable dust particles that can penetrate further into the gas-exchange region, making it the most hazardous dust component. Prolonged exposure to high concentrations of dust particles can lead to respiratory health issues for both livestock and farming staff. Ammonia, an example of a gaseous pollutant, is derived from the decomposition of nitrous compounds. Increased exposure to ammonia may also have an effect on the health of humans and livestock. There are a number of technologies available to ensure exposure to these pollutants is minimised. Through proactive means, (the optimal design and management of livestock buildings) air quality can be improved to reduce the likelihood of risks associated with sub-optimal air quality. Once air problems have taken hold, other reduction methods need to be applied utilising a more reactive approach. A key requirement for the control of concentration and exposure of airborne pollutants to an acceptable level is to be able to conduct real-time measurements of these pollutants. This paper provides a review of airborne pollution including methods to both measure and control the concentration of pollutants in livestock buildings