A wireless sensor network based low cost and energy efficient frame work for precision agriculture

Math, RajinderKumar M.; Dharwadkar, Nagaraj V.

doi:10.1109/icnte.2017.7947883

Cited by 23 publications

(10 citation statements)

References 17 publications

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“…As presented in the previous research, many projects [8][9][10][11] have been published. These implementations for IoT solutions that control irrigation systems, mainly using single nodes with Arduinos, combined with a set of environmental data sensors, have several problems due to the large amounts of wire used to spread them across the fields.…”

Section: Related Workmentioning

confidence: 99%

Water Management for Sustainable Irrigation Systems Using Internet-of-Things

Glória

Dionisio

Simões

et al. 2020

Sensors

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This paper introduces a new way of managing water in irrigation systems, which can be applied to gardens or agricultural fields, replacing human intervention with Wireless Sensor Networks. A typical irrigation system wastes on average 30% of the water used, due to poor management and configuration. This sustainable irrigation system allows a better efficiency in the process of irrigation that can lead to savings for the end user, not only monetary but also in natural resources, such as water and energy, leading to a more sustainable environment. The system can retrieve real time data and use them to determinate the correct amount of water to be used in a garden. With this solution, it is possible to save up to 34% of water when using sensor data from temperature, humidity and soil moisture, or up to 26% when using only temperature inputs. Besides a detailed system architecture, this paper includes a real case scenario implementation and results discussion.

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Section: Related Workmentioning

confidence: 99%

Water Management for Sustainable Irrigation Systems Using Internet-of-Things

Glória

Dionisio

Simões

et al. 2020

Sensors

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“…In general, most of the sensor nodes used to monitor soil data (such as temperature, humidity, and matric potential) and weather data (such as temperature and relative humidity) are operated using open, low-cost hardware platforms such as the Arduino [10][11][12][13][14] or Raspberry Pi [15][16][17]. Zigbee [11,[17][18][19], LoRa [16], Wifi [20], Bluetooth [14], GSM [12], and GPRS [21] are the predominant wireless technologies used.…”

Section: Data Gatheringmentioning

confidence: 99%

Smart & Green: An Internet-of-Things Framework for Smart Irrigation

Campos

Rocha²,

Gondim

et al. 2019

Sensors

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Irrigation is one of the most water-intensive agricultural activities in the world, which has been increasing over time. Choosing an optimal irrigation management plan depends on having available data in the monitoring field. A smart agriculture system gathers data from several sources; however, the data are not guaranteed to be free of discrepant values (i.e., outliers), which can damage the precision of irrigation management. Furthermore, data from different sources must fit into the same temporal window required for irrigation management and the data preprocessing must be dynamic and automatic to benefit users of the irrigation management plan. In this paper, we propose the Smart&Green framework to offer services for smart irrigation, such as data monitoring, preprocessing, fusion, synchronization, storage, and irrigation management enriched by the prediction of soil moisture. Outlier removal techniques allow for more precise irrigation management. For fields without soil moisture sensors, the prediction model estimates the matric potential using weather, crop, and irrigation information. We apply the predicted matric potential approach to the Van Genutchen model to determine the moisture used in an irrigation management scheme. We can save, on average, between 56.4% and 90% of the irrigation water needed by applying the Zscore, MZscore and Chauvenet outlier removal techniques to the predicted data.

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“…Based on the research survey, it is understood that the agricultural sector is heavily involved in employing IoT sensors to collect data, which later helps in data mining and predicting using various artificial intelligence (AI) techniques. However, in recent times, low-cost data gathering electronic devices are becoming popular which include Arduino [18][19][20][21][22], Raspberry Pi [23][24][25], Zigbee [19,[25][26][27], LoRa [24], WiFi [28], Bluetooth [22], Global System for Mobile (GSM) Communications [20], and General Packet Radio Service (GPRS) [29]. As well, there has been a rapid influx of commercial water sprinkling and pest spraying farming solutions embedded with above mentioned electronic devices into the market.…”

Section: Introductionmentioning

confidence: 99%

“…These commercial systems demand an efficient energy storage system for their operation; with this, the use of rechargeable and portable batteries like nickel-cadmium (NiCd), and lithium-ion (Li-ion), etc., have become popular. More recently, the on-board solar powered-battery systems also emerged, making these commercial farming solutions energy efficient [19,20]. Besides energy management, water management is crucial; hence the on-board water and chemical storage tanks should be optimally designed considering the energy requirements.…”

Section: Introductionmentioning

confidence: 99%

Design and Analysis of Photovoltaic Powered Battery-Operated Computer Vision-Based Multi-Purpose Smart Farming Robot

et al. 2021

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Farm machinery like water sprinklers (WS) and pesticide sprayers (PS) are becoming quite popular in the agricultural sector. The WS and PS are two distinct types of machinery, mostly powered using conventional energy sources. In recent times, the battery and solar-powered WS and PS have also emerged. With the current WS and PS, the main drawback is the lack of intelligence on water and pesticide use decisions and autonomous control. This paper proposes a novel multi-purpose smart farming robot (MpSFR) that handles both water sprinkling and pesticide spraying. The MpSFR is a photovoltaic (PV) powered battery-operated internet of things (IoT) and computer vision (CV) based robot that helps in automating the watering and spraying process. Firstly, the PV-powered battery-operated autonomous MpSFR equipped with a storage tank for water and pesticide drove with a programmed pumping device is engineered. The sprinkling and spraying mechanisms are made fully automatic with a programmed pattern that utilizes IoT sensors and CV to continuously monitor the soil moisture and the plant’s health based on pests. Two servo motors accomplish the horizontal and vertical orientation of the spraying nozzle. We provided an option to remotely switch the sprayer to spray either water or pesticide using an infrared device, i.e., within a 5-m range. Secondly, the operation of the developed MpSFR is experimentally verified in the test farm. The field test’s observed results include the solar power profile, battery charging, and discharging conditions. The results show that the MpSFR operates effectively, and decisions on water use and pesticide are automated.

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A wireless sensor network based low cost and energy efficient frame work for precision agriculture

Cited by 23 publications

References 17 publications

Water Management for Sustainable Irrigation Systems Using Internet-of-Things

Water Management for Sustainable Irrigation Systems Using Internet-of-Things

Smart & Green: An Internet-of-Things Framework for Smart Irrigation

Design and Analysis of Photovoltaic Powered Battery-Operated Computer Vision-Based Multi-Purpose Smart Farming Robot

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