Internet of Things (IoT) in Agriculture - Selected Aspects

Stočes, Michal; Vaněk, Jiřı́; Masner, Jan; Pavlík, Jan

doi:10.7160/aol.2016.080108

Cited by 117 publications

(48 citation statements)

References 9 publications

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“…The existing technologies such as ad-hoc systems, www.ijacsa.thesai.org pervasive and embedded systems, wearable technology and machine learning techniques are founded new concept by emerging of IoT. One of the most important requirements in this technology is connection to internet problem [16]. Internet one of the inseparable things in our life that can reduce cost and time.…”

Section: B Internet Of Thingsmentioning

confidence: 99%

Wireless Sensor Network and Internet of Things in Precision Agriculture

Kiani¹,

Seyyedabbasi²

2018

ijacsa

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Internet of Things is one of the most popular subjects nowadays where sensors and smart devices facilitate the provision of information and communication. In IoT, one of the main concepts is wireless sensor networks in which data is collected from all the sensors in a network characterized by low power consumption and a wide range of communication. In this study, an architecture to monitor soil moisture, temperature and humidity on small farms is provided. The main motivation for this study is to decrease water consumption whilst increasing productivity on small agricultural farms and precisions on them. This motivation is further propelled by the fact that agriculture is the backbone of some towns and most villages in most of the countries. Furthermore, some countries depend on farming as the main source of income. Putting the above-mentioned factors into consideration, the farm is divided into regions; the proposed system monitors soil moisture, humidity and temperature in the respective regions using wireless sensor networks, internet of things and sends a report to the end user. The report contains, as part of the information, a 10-day weather forecast. We believe that with the above information, the end user (farmer) can more efficiently schedule farm cultivation, harvesting, irrigation, and fertilization.

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Section: B Internet Of Thingsmentioning

confidence: 99%

Wireless Sensor Network and Internet of Things in Precision Agriculture

Kiani¹,

Seyyedabbasi²

2018

ijacsa

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“…Beragam aplikasi dikembangkan dengan JSN dan M2M menggunakan platform OpeMTC, di antaranya sistem deteksi kebocoran pipa air [5], sistem kota cerdas [6], dan deteksi polusi udara [7]. Aplikasi IoT pun telah dikembangkan untuk pertanian dan pertanahan [8]- [11]. Namun, sistem tersebut secara khusus digunakan untuk pemantauan sistem irigasi di lahan pertanian dan mengontrol kondisi tanah [8] dan manajemen pertanian [9]- [11].…”

Section: Pendahuluanunclassified

Sistem Pemantau Kelembapan Tanah Akurat dengan Protokol Zigbee IEEE 802.15.4 pada Platform M2M OpenMTC

Fredy

Abdurohman

2018

Jurnal Teknologi dan Sistem Komputer

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This paper presents a study on an accurate soil moisture monitoring system based on its humidity from 9 sensor nodes using wireless sensor network (WSN) and M2M platform. The system used IEEE 802.15.4 (Zigbee) protocol. The system was connected to the application via the OpenMTC M2M platform. This monitoring system can measure soil moisture accurately and provide soil water content status on the application. The system was effective in measuring soil moisture at a distance of 0-25 meters where there was a barrier between gateway and sensor, and at a distance of 0-50 meter in line of sight. The position of the sensors that are within 3 meters of each other and the depth of each sensor 3 cm can measure soil moisture properly.

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“…The IoT (Internet of Things) is an important part of the new generation of information technology. It refers to a huge network formed by combining various information sensing devices with the Internet [1]. In recent years, the widespread use of IoT terminal equipment has led to a spurt of terminal data and connections, requiring a more computationally efficient IoT network architecture to enable timely data analysis and processing.…”

Section: Introductionmentioning

confidence: 99%

IoT Implementation of Kalman Filter to Improve Accuracy of Air Quality Monitoring and Prediction

et al. 2019

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In order to obtain high-accuracy measurements, traditional air quality monitoring and prediction systems adopt high-accuracy sensors. However, high-accuracy sensors are accompanied with high cost, which cannot be widely promoted in Internet of Things (IoT) with many sensor nodes. In this paper, we propose a low-cost air quality monitoring and real-time prediction system based on IoT and edge computing, which reduces IoT applications dependence on cloud computing. Raspberry Pi with computing power, as an edge device, runs the Kalman Filter (KF) algorithm, which improves the accuracy of low-cost sensors by 27% on the edge side. Based on the KF algorithm, our proposed system achieves the immediate prediction of the concentration of six air pollutants such as SO 2 , NO 2 and PM2.5 by combining the observations with errors. In the comparison experiments with three common predicted algorithms including Simple Moving Average, Exponentially Weighted Moving Average and Autoregressive Integrated Moving Average, the KF algorithm can obtain the optimal prediction results, and root-mean-square error decreases by 68.3% on average. Taken together, the results of the study indicate that our proposed system, combining edge computing and IoT, can be promoted in smart agriculture. of industry digitalization in agile connectivity, real-time business, data optimization, application intelligence, security and privacy protection, etc. Edge computing features are like human nerve endings, which can self-process simple stimuli and feedback the processed features to the cloud brain.Smart agriculture makes the application of IoT technology in traditional agricultural production more "intelligent" by using sensors and software to control agricultural production through mobile platforms or computer platforms. In smart agriculture, establishing a real-time monitoring and prediction system for air quality (AQ) is the most basic and most important solution [5]. The prediction for AQ is based on the analysis of the monitoring data. In other words, the accuracy of the monitoring data affects the accuracy of the prediction to a certain extent [6]. At the same time, the Environment Agency also has specified specific values for AQ [7]. Once current AQ exceeds the threshold, people should take appropriate countermeasures. However, when the prediction is inaccurate, it will lead to decision errors. In order to obtain high-precision monitoring data, many AQ monitoring schemes currently existing use high-precision sensors. However, high-precision sensors are often accompanied by higher costs. A complete system consists of multiple sets of sensors [8], so there is a trade-off between cost and accuracy. In addition, in a traditional IoT-based AQ monitoring system, the data collected by the sensing layer needs to be uploaded, analyzed and processed in the cloud computing platform at the network layer [9]. However, in China, most agricultural areas are in remote locations and harsh environments limited by bandwidth and network connectivity [10]. The timely ...

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Internet of Things (IoT) in Agriculture - Selected Aspects

Cited by 117 publications

References 9 publications

Wireless Sensor Network and Internet of Things in Precision Agriculture

Wireless Sensor Network and Internet of Things in Precision Agriculture

Sistem Pemantau Kelembapan Tanah Akurat dengan Protokol Zigbee IEEE 802.15.4 pada Platform M2M OpenMTC

IoT Implementation of Kalman Filter to Improve Accuracy of Air Quality Monitoring and Prediction

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