Wireless sensor network in precision farming for forecasting and monitoring of apple disease: a survey

Nabi, Firasath; Jamwal, Sanjay; Padmanbh, Kumar

doi:10.1007/s41870-020-00418-8

Cited by 24 publications

(15 citation statements)

References 24 publications

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“…In addition, they analyze a case study on a smart farm prototype, based on IoT data, as an integrated food, energy, and water (FEW) system. Nabi et al [14] present a comparative study of different studies to provide a deeper insight into these implemented systems. They also present a study of apple disease prognostic systems, highlighting their key characteristics and drawbacks.…”

Section: Related Workmentioning

confidence: 99%

A Wireless Sensor Network Deployment for Soil Moisture Monitoring in Precision Agriculture

Lloret

Sendra

García

et al. 2021

Sensors

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The use of precision agriculture is becoming more and more necessary to provide food for the world’s growing population, as well as to reduce environmental impact and enhance the usage of limited natural resources. One of the main drawbacks that hinder the use of precision agriculture is the cost of technological immersion in the sector. For farmers, it is necessary to provide low-cost and robust systems as well as reliability. Toward this end, this paper presents a wireless sensor network of low-cost sensor nodes for soil moisture that can help farmers optimize the irrigation processes in precision agriculture. Each wireless node is composed of four soil moisture sensors that are able to measure the moisture at different depths. Each sensor is composed of two coils wound onto a plastic pipe. The sensor operation is based on mutual induction between coils that allow monitoring the percentage of water content in the soil. Several prototypes with different features have been tested. The prototype that has offered better results has a winding ratio of 1:2 with 15 and 30 spires working at 93 kHz. We also have developed a specific communication protocol to improve the performance of the whole system. Finally, the wireless network was tested, in a real, cultivated plot of citrus trees, in terms of coverage and received signal strength indicator (RSSI) to check losses due to vegetation.

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Section: Related Workmentioning

confidence: 99%

A Wireless Sensor Network Deployment for Soil Moisture Monitoring in Precision Agriculture

Lloret

Sendra

García

et al. 2021

Sensors

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“…Agriculture produces most of the world's food and goods. Climate change and agriculture are interdependent processes whose negative effects of climate change affect agriculture both directly and indirectly [1][2][3][4]. In the growth of agriculture face different encounter in climate changes.…”

Section: Introductionmentioning

confidence: 99%

Weather Prediction based on Wireless Sensor Network and Internet of Things with Analysis using Hybrid SSOA with MA

A.S.²

2022

Preprint

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Weather forecasting is a growing area that predicts the weather that will occur in a particular place at a particular time. Weather forecasting is considered to be the most important part of research where many real-time issues arise. These are the requirements for wireless sensor networks to detect the weather. In this article we propose using the Mayfly Algorithm (MA) hybrid algorithm with Shuffled Shepherd Optimization Algorithm (SSOA). Experimental tasks are carried out with a set of climate data. Based on climatic parameters such as temperature, humidity and clouds, the data is divided into heat, wind and rain. From the result obtained, it is predicted that the weather will prove the proposed qualification methods at the level of accuracy. The result shows that the hybridized SSOA and MA method is efficient and accurate in predicting weather conditions. This experimental result is carried out by using Wireless Sensors Network and IoT on agricultural land.

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“…Especially in the dry season, there is often a shortage of water, and production results are not optimal, so applying the precision agricultural approach through technology is necessary. Precision agriculture is a management concept that uses minimal input resources to produce higher outputs [8]. Precision agriculture is based on monitoring, analyzing, and managing parameters related to agriculture.…”

Section: Introductionmentioning

confidence: 99%

Development of Irrigation Monitoring and Control Systems to Support the Implementation of the System of Rice Intensification (SRI)

Saputra¹,

Nugroho²,

Murtiningrum³

et al. 2022

Proceedings of the 2nd International Conference on Smart and Innovative Agriculture (ICoSIA 2021)

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Indonesia is a tropical country with high average annual rainfall. The occurrence of unpredictable world climate changes makes it difficult to determine the planting schedule. Farmers often experience crop failure due to a lack of water during the dry season. To overcome these problems, it is necessary to apply the precision farming approach to maximize output with minimal input through technology. SRI (System of Rice Intensification) is one of the innovations in rice cultivation that approaches the concept of precision agriculture. SRI can increase rice production and also save water use. However, SRI irrigation still uses intermittent irrigation based on human intuition and is done manually. Therefore, it is necessary to develop an irrigation monitoring and control system for SRI based on environmental conditions of growth represented by reference Evapotranspiration (ETo) and soil moisture content. This study aims to develop a monitoring and control system for SRI irrigation based on ETo and soil moisture content. To accommodate ETo and soil moisture content, a model using fuzzy logic was developed. This system has a solar radiation sensor, temperature sensor, soil moisture sensor, proximity sensor, Arduino mega 2560, pump, chamber, and drum. The working stages of the system begin with the reading of environmental conditions by the sensor. Furthermore, the reading results will be processed by fuzzy logic as irrigation decision-making. The data obtained from the monitoring of Evapotranspiration, soil moisture content, water level are used to present the growing environmental conditions. Water use efficiency data is used to compare the performance of the SRI system using fuzzy and non-fuzzy logic. The results of irrigation efficiency show that the SRI system using fuzzy can save water up to 52.08% compared to SRI without fuzzy.

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Wireless sensor network in precision farming for forecasting and monitoring of apple disease: a survey

Cited by 24 publications

References 24 publications

A Wireless Sensor Network Deployment for Soil Moisture Monitoring in Precision Agriculture

A Wireless Sensor Network Deployment for Soil Moisture Monitoring in Precision Agriculture

Weather Prediction based on Wireless Sensor Network and Internet of Things with Analysis using Hybrid SSOA with MA

Development of Irrigation Monitoring and Control Systems to Support the Implementation of the System of Rice Intensification (SRI)

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