scholarly journals IoT Based Automatic Soil Moisture Monitoring System using Raspberry PI

2019 ◽  
Vol 9 (2) ◽  
pp. 4375-4379 ◽  
Keyword(s):  
Soil Moisture ◽  
Internet Of Things ◽  
Water Level ◽  
Soil Water ◽  
Monitoring System ◽  
Irrigation System ◽  
Irrigation Scheduling ◽  
Advanced Technology ◽  
Raspberry Pi ◽  
The World

Internet of Things (IoT) is an advanced technology for monitoring and controlling device anywhere in the world. It can connect devices with living things. Agriculture is one of the major sectors which contribute a lot to the financial of India and to get quality product, proper irrigation has to be performed, to reduce man power using modern technology of internet of things IoT in today’s life. Soil moisture is an integral part of plant life, which directly affects crop growth and yield, as well as irrigation scheduling. This system will be a substitute to traditional farming method. We will develop such a system that will help a farmer to know his field status in his home or he may be residing in any part of the world. It proposes an automatic irrigation system for the agricultural lands. Currently the automation is one of the important roles in the human life. It is not only provides comfort but also efficiency and time saving. So here it is also designs a smart irrigation technology by using raspberry pi and connecting to the weather API. Raspberry-pi is the main heart of the whole system. An automated irrigation system was developed to optimize water use for agricultural crops. Automation allows us to control appliances automatically. The objectives of this to control the water motor automatically, To monitor the soil, water level using weather API.A robotized irrigation system framework might have been created should streamline water utilize to agriculture crops. Mechanization permits us with control appliances naturally. Those targets for this on control those water motor naturally monitor the soil, water level utilizing weather API In previously we are using the soil moisture control by using some set of sensors by this water is pumping continuously even though it is rainy.so by this over flow of the water is taken place to overcome this problem we are using the cloud monitoring system based on the weather conditions.

scholarly journals Investigation of Effective Irrigation Strategies for High-Density Apple Orchards in Pennsylvania

Agronomy ◽  
2021 ◽  
Vol 11 (4) ◽  
pp. 732
Author(s):  
Xiaohu Jiang ◽  
Long He
Keyword(s):  
Soil Moisture ◽  
Soil Water ◽  
Fruit Quality ◽  
Irrigation System ◽  
Soil Water Potential ◽  
Irrigation Scheduling ◽  
Apple Orchard ◽  
High Density ◽  
Apple Orchards ◽  
Conventional Methods

Irrigation helps grow agricultural crops in dry areas and during periods of inadequate rainfall. Proper irrigation could improve both crop productivity and produce quality. For high density apple orchards, water relations are even more important. Most irrigation in tree fruit orchards is applied based on grower’s experience or simple observations, which may lead to over- or under-irrigation. To investigate an effective irrigation strategy in high-density apple orchard, three irrigation methods were tested including soil moisture-based, evapotranspiration (ET)-based and conventional methods. In soil moisture-based irrigation, soil water content and soil water potential sensors were measured side by side. In ET-based irrigation, daily ET (ETc) and accumulated water deficit were calculated. Conventional method was based on the experience of the operator. The experiment was conducted from early June through middle of October (one growing season). Lastly, water consumption, fruit yield and fruit quality were analyzed for these irrigation strategies. Results indicated that the soil moisture-based irrigation used least water, with 10.8% and 4.8% less than ET-based and conventional methods, respectively. The yield from the rows with the soil moisture-based irrigation was slightly higher than the other two, while the fruit quality was similar. The outcome from this study proved the effectiveness of using soil moisture sensors for irrigation scheduling and could be an important step for future automatic irrigation system.

scholarly journals RANCANG BANGUN SISTEM MONITORING KETINGGIAN AIR DAN KELEMBABAN TANAH PADA PENYIRAM TANAMAN OTOMATIS DENGAN HMI (HUMAN MACHINE INTERFACE) BERBASIS RASPBERRY PI MENGGUNAKAN SOFTWARE NODE-RED

2017 ◽  
Vol 19 (3) ◽  
pp. 1
Author(s):  
Esa Hayyu Wiguna ◽  
Arkhan Subari
Keyword(s):  
Soil Moisture ◽  
Water Level ◽  
Monitoring System ◽  
Touch Screen ◽  
Human Machine Interface ◽  
Raspberry Pi ◽  
Plant Design ◽  
Error Ratio ◽  
Machine Interface ◽  
Technical Specifications

Esa Hayyu Wiguna, Arkhan Subari, in this paper explain that the monitoring system is a system used to monitor and control work processes in a plant design. This system is widely used and applied in the industrial world to find out the performance of a plant. To do the monitoring system, a lot of software can be used, which is then called the HMI (Human Machine Interface). The monitoring system with an interface in the form of HMI can be presented in various forms, such as buttons, or can also be displayed in the visualization of the plant while working. This monitoring system through an HMI interface uses supporting hardware in the form of a Raspberry Pi as a device to process the data that will be displayed on the display screen, while displaying its visualization uses an LCD touch screen. This LCD touch screen is connected to the Raspberry Pi via the LCD driver. The graphic form that will be displayed on the LCD touch screen is designed using Node-RED software. The visualization that will be displayed on the Touch Screen LCD will be adjusted to the working system of automatic plant sprinklers. This monitoring system using an HMI interface can display the plant's working system through indicators of water level and soil moisture. To test tube 2 water level measured through ultrasonic sensors through HMI has an error ratio of 1.01%, while for soil moisture measured through soil moisture sensors has an error ratio of 1.51%. Keywords: Monitoring System, Human Machine Interface (HMI), Raspberry Pi, Node-RED. ReferencesHaryanto, Heri dan Sarif Hidayat. 2012. Perancangan HMI (Human Machine Interface) Untuk Pengendalian Kecepatan Motor DC. Jurnal S1 Jurusan Elektro Fakultas Teknik Terpublikasi. Banten: Universitas Sultan Ageng Tirtayasa.Udayana, Gede Agus, I Gede Mahendra Darmawiguna, dan I Made Gede Sumarya. 2016. Pengembangan Prototipe Portal Otomatis Dengan Pendeteksian Plat Nomor Kendaraan Berbasis Raspberry Pi. Artikel Jurusan Pendidikan Teknik Informatika Terpublikasi. Bali: Universitas Pendidikan Ganesha.Man, Joseph. 2016. Raspberry Pi 3 Model B Technical Specifications. https://www.element14.com/community/docs/DOC-80899/l/raspberry-pi-3-model-b-technical-specifications. Diakses tanggal 14 Agustus 2017.Kurniawan, Halim. 2005. Aplikasi Penjawab Pesan Singkat Automatis dengan Bahasa Python. Makalah Seminar Tugas Akhir S1 Jurusan Teknik Elektro Terpublikasi. Semarang: Universitas Diponegoro.Node-RED. 2013. Node-RED; Flow-based programming for the Internet of Things. https://nodered.org/. Diakses tanggal 02 Mei 2017.Tim J, M. 2016. Developing with Node-RED. https://software.intel.com/en-us/articles/developing-with-node-red. Diakses tanggal 02 Mei 2017.

scholarly journals Design and Development of an Automatic Prototype Smart Irrigation Model

2021 ◽  
pp. 119-127
Keyword(s):  
Soil Moisture ◽  
Water Level ◽  
Irrigation System ◽  
Human Resources Management ◽  
Ultrasonic Sensor ◽  
Moisture Level ◽  
Moisture Sensor ◽  
Soil Moisture Level ◽  
Input Signals ◽  
Crop Field

In the current condition, it is difficult to increase plant development and reduce expenses in agricultural sectors; nevertheless, an advanced thought leads to the use of an automated model that introduces automation in the irrigation system, which can aid in improved water and human resources management. An automated model has been developed using sensors and microcontroller technology, to make the most efficient use of water supply for irrigation. A soil moisture content detector is inserted into the soil of the crops, and an ultrasonic sensor is placed above the soil of the crops to measure the water level after irrigation has begun. A C++ program with threshold values for the moisture sensor was used to start the system in the crop field depending on the soil moisture level, and an ultrasonic sensor was used to control the water in the crop field. The Arduino UNO board is a microcontroller inbuilt of Atmel in the mega AVR family (ATMega328) and the sensors were used to lead the model in turning ON/OFF. A microcontroller was included in this model to run the program by receiving sensor input signals and converting them to soil water content and water level values in the crop field. The microcontroller began by receiving input values, which resulted in an output instructing the relay to turn on the groundwater pump. An LCD screen has also been interfaced with the microcontroller to show the percentage of moisture in the soil, field water level, and pump condition. When the soil moisture level reaches 99 percent and the water level reaches 6 cm after 2.5 and 4 minutes, respectively, the pump is turned off. This model, according to the study, might save water, time, and reduce human effort.

scholarly journals Design a Monitoring and Control in Irrigation Systems using Arduino Wemos with the Internet of Things

2021 ◽  
Vol 1 (1) ◽  
pp. 53-64
Author(s):  
Lukman Medriavin Silalahi ◽  
Setiyo Budiyanto ◽  
Freddy Artadima Silaban ◽  
Arif Rahman Hakim
Keyword(s):  
Soil Moisture ◽  
Water Level ◽  
Irrigation System ◽  
Ground Level ◽  
Prototype System ◽  
Monitoring And Control ◽  
Moisture Sensor ◽  
Turn On ◽  
Soil Moisture Sensors ◽  
Level Sensor

Irrigation door is a big issue for farmers. The factor that became a hot issue at the irrigation gate was the irresponsible attitude of the irrigation staff regarding the schedule of opening/closing the irrigation door so that it caused the rice fields to becoming dry or submerged. In this research, an automatic prototype system for irrigation system will be designed based on integrating several sensors, including water level sensors, soil moisture sensors, acidity sensors. This sensor output will be displayed on Android-based applications. The integration of communication between devices (Arduino Nano, Arduino Wemos and sensors supporting the irrigation system) is the working principle of this prototype. This device will control via an Android-based application to turn on / off the water pump, to open/close the irrigation door, check soil moisture, soil acidity in real time. The pump will automatically turn on based on the water level. This condition will be active if the water level is below 3cm above ground level. The output value will be displayed on the Android-based application screen and LCD screen. Based on the results of testing and analysis of the prototype that has been done in this research, the irrigation door will open automatically when the soil is dry. This condition occurs if the water level is less than 3 cm. The calibrated Output value, including acidity sensor, soil moisture sensor and water level sensor, will be sent to the server every 5 seconds and forwarded to an Android-based application as an output display.

scholarly journals Design and Analysis of Trash Monitoring System Prototype Based On Internet of Things (IoT) Using MQTT Protocol

2018 ◽  
Vol 10 (3) ◽  
pp. 113
Author(s):  
Achmad Auliyaa Zulfikri ◽  
Doan Perdana ◽  
Gustommy Bisono
Keyword(s):  
Internet Of Things ◽  
Monitoring System ◽  
System Performance ◽  
Performance Test ◽  
Advanced Technology ◽  
Android Application ◽  
Packet Delivery ◽  
End To End Delay ◽  
System Prototype ◽  
Maximum Limit

On this research,Internet of Things (IoT) as an advanced technology is used to monitor the height of trash from a trash can in order to give notification whether the height of trash is already reach the maximum limit or not yet.To support those needs,we used NodeMCU as microcontroller,ultrasonic sensor,MQTT as IoT protocol,and also Android application to show the data.After we did the system performance test,we got the biggest result of end-to-end delay which is 2.06875 seconds when the packet delivery is set to 1000 ms with 3 active nodes and the smallest result which is 0.26055 seconds when the packet delivery is set to 100 ms with 1 active mode.The biggest result of throughput is 597.17 Bytes/s when the packet delivery is set to 100 ms with 1 active mode and the smallest result is 75.86 Bytes/s when the packet delivery is set to 1000 ms with 3 active nodes.The biggest result of availability and reliability is 99.905% when the packet delivery is set to 1000 ms and the smallest result is 99.833% when the packet delivery is set to 100 ms.

Soybean Irrigation Initiation in Mississippi: Yield, Soil Moisture, and Economic Response

2019 ◽  
Vol 35 (1) ◽  
pp. 39-50
Author(s):  
H. C. Pringle, III ◽  
L. L. Falconer ◽  
D. K. Fisher ◽  
L. J. Krutz
Keyword(s):  
Soil Moisture ◽  
Water Potential ◽  
Soil Water ◽  
Water Deficit ◽  
Mississippi Delta ◽  
Soil Water Potential ◽  
Irrigation Scheduling ◽  
Silty Clay ◽  
Soil Water Deficit ◽  
Soybean Yield

Abstract. Irrigated acreage is expanding and groundwater supplies are decreasing in the Mississippi Delta. Efficient irrigation scheduling of soybean [ (L.) Merr] will aid in conservation efforts to sustain groundwater resources. The objective of this study was to develop irrigation initiation recommendations for soybean grown on Mississippi Delta soils. Field studies were conducted on a deep silty clay (SiC) in 2012, 2013, 2014, and 2015 and on a deep silty clay loam (SiCL) and deep silt loam (SiL) or loam (L) soil in 2013, 2014, and 2015. Irrigation was initiated multiple times during the growing season and soybean yield and net return were determined to evaluate the effectiveness of each initiation timing. Growth stage, soil water potential (SWP), and soil water deficit (SWD) were compared at these initiation timings to determine which parameter or combination of parameters consistently predicted the resulting greatest yields and net returns. Stress conditions that reduce yield can occur at any time from late vegetative stages to full seed on these deep soils. The wide range of trigger values found for SWP and SWD to increase yields in different years emphasizes the complexity of irrigation scheduling. Monitoring soil moisture by itself or use of a single trigger value is not sufficient to optimize irrigation scheduling to maximize soybean yield with the least amount of water every year on these soils. Monitoring one or more parameters (e.g., leaf water potential, canopy temperature, air temperature, humidity, solar radiation, and wind) is needed in conjunction with soil moisture to directly or indirectly quantify the abiotic stresses on the plant to better define when a yield reducing stress is occurring. Keywords: Irrigation initiation, Irrigation scheduling, Soil water deficit, Soil water potential, Soybean, Water conservation.

scholarly journals Soil Moisture Sensor Test with Mississippi Delta Soils

2019 ◽  
Vol 62 (2) ◽  
pp. 363-370
Author(s):  
Ruixiu Sui ◽  
Horace C. Pringle ◽  
Edward M. Barnes
Keyword(s):  
Soil Moisture ◽  
Soil Temperature ◽  
Water Potential ◽  
Water Content ◽  
Soil Water ◽  
Measurement Accuracy ◽  
Mississippi Delta ◽  
Soil Water Potential ◽  
Gravimetric Method ◽  
Irrigation Scheduling

Abstract. One of the methods for irrigation scheduling is to use sensors to measure the soil moisture level in the plant root zone and apply water if there is a water shortage for the plants. The measurement accuracy and reliability of the soil moisture sensors are critical for sensor-based irrigation management. This study evaluated the measurement accuracy and repeatability of the EC-5 and 5TM soil volumetric water content (SVWC) sensors, the MPS-2 and 200SS soil water potential (SWP) sensors, and the 200TS soil temperature sensor. Six 183 cm × 183 cm × 71 cm wooden compartments were built inside a greenhouse, and each compartment was filled with one type of soil from the Mississippi Delta. A total of 66 sensors with 18 data loggers were installed in the soil compartments to measure SVWC, SWP, and soil temperature. Soil samples were periodically collected from the compartments to determine SVWC using the gravimetric method. SVWC measured by the sensors was compared with that determined by the gravimetric method. The SVWC readings from the sensors had a linear regression relationship with the gravimetric SVWC (r2 = 0.82). This relationship was used to calibrate the sensor readings. The SVWC and SWP sensors could detect the general trend of soil moisture changes. However, their measurements varied significantly among the sensors. To obtain accurate absolute soil moisture measurements, the sensors require individual and soil-specific calibration. The 5TM, MPS-2, and 200TS sensors performed well in soil temperature measurement tests. Individual temperature readings from these sensors were very close to the mean of all sensor readings. Keywords: Irrigation, Sensors, Soil types, Soil water content, Soil water potential.

Evaluation of a soil moisture sensor to reduce water and nutrient leaching in turfgrass (Cynodon dactylon cv. Wintergreen)

2007 ◽  
Vol 47 (2) ◽  
pp. 215 ◽  
Author(s):  
S. M. Pathan ◽  
L. Barton ◽  
T. D. Colmer
Keyword(s):  
Soil Moisture ◽  
Cynodon Dactylon ◽  
Irrigation System ◽  
Irrigation Scheduling ◽  
Couch Grass ◽  
Moisture Sensor ◽  
Soil Moisture Sensor ◽  
Application Rates ◽  
Controlled Irrigation ◽  
Conventional Irrigation

This study evaluated water application rates, leaching and quality of couch grass (Cynodon dactylon cv. Wintergreen) under a soil moisture sensor-controlled irrigation system, compared with plots under conventional irrigation scheduling as recommended for domestic lawns in Perth, Western Australia by the State’s water supplier. The cumulative volume of water applied during summer to the field plots of turfgrass with the sensor-controlled system was 25% less than that applied to plots with conventional irrigation scheduling. During 154 days over summer and autumn, about 4% of the applied water drained from lysimeters in sensor-controlled plots, and about 16% drained from lysimeters in plots with conventional irrigation scheduling. Even though losses of mineral nitrogen via leaching were extremely small (representing only 1.1% of the total nitrogen applied to conventionally irrigated plots), losses were significantly lower in the sensor-controlled plots. Total clippings produced were 18% lower in sensor-controlled plots. Turfgrass colour in sensor-controlled plots was reduced during summer, but colour remained acceptable under both treatments. The soil moisture sensor-controlled irrigation system enabled automatic implementation of irrigation events to match turfgrass water requirements.

Area-representative validation of remotely sensed high resolution soil moisture using a cosmic-ray neutron sensor

2020 ◽  
Author(s):  
Dragana Panic ◽  
Isabella Pfeil ◽  
Andreas Salentinig ◽  
Mariette Vreugdenhil ◽  
Wolfgang Wagner ◽  
...  
Keyword(s):  
Soil Moisture ◽  
Soil Water ◽  
Root Zone ◽  
Spatial Scales ◽  
Temporal Frequency ◽  
Cosmic Ray ◽  
Irrigation Scheduling ◽  
Water Index ◽  
The Impact

<p>Reliable measurements of soil moisture (SM) are required for many applications worldwide, e.g., for flood and drought forecasting, and for improving the agricultural water use efficiency (e.g., irrigation scheduling). For the retrieval of large-scale SM datasets with a high temporal frequency, remote sensing methods have proven to be a valuable data source. (Sub-)daily SM is derived, for example, from observations of the Advanced Scatterometer (ASCAT) since 2007. These measurements are available on spatial scales of several square kilometers and are in particular useful for applications that do not require fine spatial resolutions but long and continuous time series. Since the launch of the first Sentinel-1 satellite in 2015, the derivation of SM at a spatial scale of 1 km has become possible for every 1.5-4 days over Europe (SSM1km) [1]. Recently, efforts have been made to combine ASCAT and Sentinel-1 to a Soil Water Index (SWI) product, in order to obtain a SM dataset with daily 1 km resolution (SWI1km) [2]. Both datasets are available over Europe from the Copernicus Global Land Service (CGLS, https://land.copernicus.eu/global/). As the quality of such a dataset is typically best over grassland and agricultural areas, and degrades with increasing vegetation density, validation is of high importance for the further development of the dataset and for its subsequent use by stakeholders.</p><p>Traditionally, validation studies have been carried out using in situ SM sensors from ground networks. Those are however often not representative of the area-wide satellite footprints. In this context, cosmic-ray neutron sensors (CRNS) have been found to be valuable, as they provide integrated SM estimates over a much larger area (about 20 hectares), which comes close to the spatial support area of the satellite SM product. In a previous study, we used CRNS measurements to validate ASCAT and S1 SM over an agricultural catchment, the Hydrological Open Air Laboratory (HOAL), in Petzenkirchen, Austria. The datasets were found to agree, but uncertainties regarding the impact of vegetation were identified.</p><p>In this study, we validated the SSM1km, SWI1km and a new S1-ASCAT SM product, which is currently developed at TU Wien, using CRNS. The new S1-ASCAT-combined dataset includes an improved vegetation parameterization, trend correction and snow masking. The validation has been carried out in the HOAL and on a second site in Marchfeld, Austria’s main crop producing area. As microwaves only penetrate the upper few centimeters of the soil, we applied the soil water index concept [3] to obtain soil moisture estimates of the root zone (approximately 0-40 cm) and thus roughly corresponding to the depth of the CRNS measurements. In the HOAL, we also incorporated in-situ SM from a network of point-scale time-domain-transmissivity sensors distributed within the CRNS footprint. The datasets were compared to each other by calculating correlation metrics. Furthermore, we investigated the effect of vegetation on both the satellite and the CRNS data by analyzing detailed information on crop type distribution and crop water content.</p><p>[1] Bauer-Marschallinger et al., 2018a: https://doi.org/10.1109/TGRS.2018.2858004<br>[2] Bauer-Marschallinger et al., 2018b: https://doi.org/10.3390/rs10071030<br>[3] Wagner et al., 1999: https://doi.org/10.1016/S0034-4257(99)00036-X</p>

scholarly journals IoT based Raspberry Pi Crop Vandalism Prevention system

2019 ◽  
Vol 9 (1) ◽  
pp. 3188-3192 ◽  
Keyword(s):  
Soil Moisture ◽  
Food Production ◽  
Irrigation System ◽  
Protection System ◽  
Population Increase ◽  
Raspberry Pi ◽  
Agricultural Fields ◽  
Important Process ◽  
Prevention System ◽  
Automated Irrigation System

Agriculture is a major source of food production in our country. Growth in population increase the demand for food production and agriculture is the main source. Irrigation in agriculture is an important process that affects the development of crops. In particular, farmers visit their agricultural fields regularly to check the level of soil moisture and water is pumped by motors to irrigate their respective fields on the basis of requirements. But the limitation of protecting crops from animals becomes a major concern for yield. This works presents the protection system in addition to the automated irrigation system.

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