The Impact of Wireless Sensor Network in the Field of Precision Agriculture: A Review

Kumar, S. Ananda; Paramasivam, Ilango

doi:10.1007/s11277-017-4890-z

Cited by 117 publications

(65 citation statements)

References 27 publications

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“…WSNs are a novel and interesting manifestation of the IoT technology [10][11][12]. With respect to the traditional wired sensors networks, the WSNs are low-cost and small size; have short deployment time; can include a higher number of sensors; ensure a robust digital transmission of the information, but also have an acceptable data rate [9,13]; and, finally, can be integrated with several different technologies and devices, such as micro electromechanical systems (MEMS) [6] or radiofrequency identification (RFID) technology [14,15]. MEMS and RFID sensors for several physical quantities such as pressure, temperature, humidity, acceleration and concentrations of chemicals and volatile compounds are currently available; thus, ensuring a multi-variable monitoring in the industrial process of interest [5,6,10,[13][14][15].…”

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confidence: 99%

A Wireless Sensors Network for Monitoring the Carasau Bread Manufacturing Process

et al. 2019

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This work copes with the design and implementation of a wireless sensors network architecture to automatically and continuously monitor, for the first time, the manufacturing process of Sardinian Carasau bread. The case of a traditional bakery company facing the challenge of the Food-Industry 4.0 competitiveness is investigated. The process was analyzed to identify the most relevant variables to be monitored during the product manufacturing. Then, a heterogeneous, multi-tier wireless sensors network was designed and realized to allow the real-time control and the data collection during the critical steps of dough production, sheeting, cutting and leavening. Commercial on-the-shelf and cost-effective integrated electronics were employed, making the proposed approach of interest for many practical cases. Finally, a user-friendly interface was provided to enhance the understanding, control and to favor the process monitoring. With the wireless senors network (WSN) we designed, it is possible to monitor environmental parameters (temperature, relative humidity, gas concentrations); cinematic quantities of the belts; and, through a dedicated image processing system, the morphological characteristics of the bread before the baking. The functioning of the WSN was demonstrated and a statistical analysis was performed on the variables monitored during different seasons. offered by Internet-of-Things (IoT) solutions to meet sustainability (or waste reduction) criteria [2]. The food industry is managing critical changes related to consumer needs, to health and safety concerns and to the demand of food products which should be differentiated and high-quality [5]. However, the quality of these products can change suddenly during the production process; thus, leading to the need for ad hoc, reliable and real-time strategies to monitor the manufacturing process [5,6]. Therefore, to satisfy customer demands, the digital monitoring of the supply chain is required to provide a deep knowledge of the crucial production steps, in order to detect the weaknesses of and permit the optimization of the whole process, to reduce the maintenance difficulties and lower the costs [5,6]. Moreover, this digitalization trend in food industry can favor the automatic data collection, the lowering of paperwork and the enabling the development of real-time, robust feedback strategies [2]. Furthermore, the challenge of ensuring acceptable adoption costs of new information and communication technologies (ICT) by small and medium size activities calls for a reasonable and effective answers [4].As a solution to these problems, the use of wireless senors networks (WSNs) was proposed [4]. WSNs are recognized as a relevant technology of the 21st century. A WSN can be defined as a low-cost platform which connects large networks of sensors [7][8][9]. They are systems which comprise radio-frequency (RF) transceivers, sensors, micro-controller or processor and power sources [5,6]. WSNs are a novel and interesting manifestation of the IoT technology [10][11][12]....

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confidence: 99%

A Wireless Sensors Network for Monitoring the Carasau Bread Manufacturing Process

et al. 2019

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“…Until recently, these domains faced many challenges, mainly due to the lack of wide-area connectivity, energy resources and sometimes harsh environmental conditions that made difficult or even impossible the deployment of WSNs. Innovative and cutting-edge technological advances, however, have paved the way for new low-cost wireless technologies, e.g., ZigBee [43], that take us to places previously unexplored, allowing us to test, administrate and record the dynamics of such systems in secure and credible ways [44].…”

Section: Wsns In the Agricultural Domainmentioning

confidence: 99%

Wireless Sensor Network Synchronization for Precision Agriculture Applications

et al. 2020

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The advent of Internet of Things has propelled the agricultural domain through the integration of sensory devices, capable of monitoring and wirelessly propagating information to producers; thus, they employ Wireless Sensor Networks (WSNs). These WSNs allow real time monitoring, enabling intelligent decision-making to maximize yields and minimize cost. Designing and deploying a WSN is a challenging and multivariate task, dependent on the considered environment. For example, a need for network synchronization arises in such networks to correlate acquired measurements. This work focuses on the design and installation of a WSN that is capable of facilitating the sensing aspects of smart and precision agriculture applications. A system is designed and implemented to address specific design requirements that are brought about by the considered environment. A simple synchronization scheme is described to provide time-correlated measurements using the sink node’s clock as reference. The proposed system was installed on an olive grove to assess its effectiveness in providing a low-cost system, capable of acquiring synchronized measurements. The obtained results indicate the system’s overall effectiveness, revealing a small but expected difference in the acquired measurements’ time correlation, caused mostly by serial transmission delays, while yielding a plethora of relevant environmental conditions.

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“…'Remote sensing' involves observation and measurement of specific object features or target from long distance. Besides 'Proximal sensing' consists of the monitoring activity working in a close range or in contact with the area of measure (Proffitt et al, 2006;Kumar and Ilango, 2018). Sensor Fusion (SF) is a specialized technique of DF in agreement with information merging from two or more sensors (Klein, 2004;Gustafsson, 2010;Ji et al, 2017).…”

Section: Sensor Fusionmentioning

confidence: 99%

Assessment of data fusion oriented on data mining approaches to enhance precision agriculture practices aimed at increase of Durum Wheat (Triticum turgidum L. var. durum) yield

D’Accolti¹,

Maggio²,

Massaro³

et al. 2018

J Food Nut Agri

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In 2050, world population will reach a total of 9 billion inhabitants and their food demand have to be satisfied. Durum wheat (Triticum turgidum L. var. durum) is one of the most important food crop and its consumption is increasing worldwide. Productivity growth in agriculture and profitable returns are strongly influenced by investment in research and development, where Precision Agriculture (PA) represents an innovative way to manage farms by introducing the Information and Communication Technology (ICT) into the production process. It is known that farms activities produce large amounts of data. Today ICT allows, with electronic and software systems, to collect and transfer automatically these data, thus increasing yields and profits. In this direction significant data are processed from agricultural production, and retrieved to extract useful information important to increase the knowledge base. Data from multiple data sources can be processed by a Data Fusion (DF) approach able to combine multiple data sources into an unique database system. Raw data are transformed into useful information, thus DF improves pattern recognition, analysis of growth factors, and relationship between crops and environments. Data Fusion is synonym of Data Integration, Sensor Fusion, and Image Fusion. By means of Data Mining (DM) it is possible to extract useful information from data of the production processes thus providing new outputs concerning product quality and product “health status”. The following literature take into account the DF and DM techniques applied to Precision Agriculture (PA) and to cultivation inputs (water, nitrogen, etc.) management. We report also last advances of DF and DM in modern agriculture and in precision durum wheat production.

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The Impact of Wireless Sensor Network in the Field of Precision Agriculture: A Review

Cited by 117 publications

References 27 publications

A Wireless Sensors Network for Monitoring the Carasau Bread Manufacturing Process

A Wireless Sensors Network for Monitoring the Carasau Bread Manufacturing Process

Wireless Sensor Network Synchronization for Precision Agriculture Applications

Assessment of data fusion oriented on data mining approaches to enhance precision agriculture practices aimed at increase of Durum Wheat (Triticum turgidum L. var. durum) yield

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