ReviewWireless sensor networks for agriculture: The state-of-the-art in practice and future challenges
Introduction
Modern day farming demands increased production of food to accommodate the large global population. Towards this goal, new technologies and solutions (Chen et al., 2015, Misra et al., 2015, Goumopoulos et al., 2014, Amaral et al., 2014, Ngo et al., 2014, Ullah et al., 2014, Misra et al., 2014, Qu et al., 2014, Misra et al., 2013, Riquelme et al., 2009, Garcia-Sanchez et al., 2011, Camilli et al., 2007) are being applied in this domain to provide an optimal alternative to gather and process information (Behzadan et al., 2014, Dhurandher et al., 2014) to enhance productivity. Moreover, the alarming climate change and scarcity of water (Postel, 1999, Bouwer, 2000, Saleth and Dinar, 2000, Jury and, 2007, Falloon and Betts, 2010, Mueller et al., 2012) demand new and improved methods for modern agricultural fields. Consequently, the need for automation and intelligent decision making is becoming more important to accomplish this mission (ur Rehman et al., 2014, Suprem et al., 2013, Wang et al., 2006, Hart and Martinez, 2006). In this regard, technologies such as ubiquitous computing (Burrell et al., 2004), wireless ad-hoc and sensor networks (Diallo et al., 2015, Srbinovska et al., 2015, Zhao et al., 2013, Karim et al., 2013, Zhang et al., 2013, Krishna et al., 2012, Zhang and Zhang, 2012, Misra et al., 2011, Mirabella and Brischetto, 2011, Lloret et al., 2011, Garcia et al., 2010, Bri et al., 2009, Lloret et al., 2009, Lin et al., 2008, Wang et al., 2006), Radio Frequency Identifier (RFID) (Ruiz-Garcia and Lunadei, 2011), cloud computing (Ojha et al., 2014, Misra et al., 2014, Cho et al., 2012), Internet of Things (IoT) (Atzori et al., 2010, Gubbi et al., 2013), satellite monitoring (Moghaddam et al., 2010), remote sensing (Bastiaanssen et al., 2000, Morais et al., 2008, Ye et al., 2013), context-aware computing (Moghaddam et al., 2010) are becoming increasingly popular.
Among all these technologies, the agriculture domain is mostly explored concerning the application of WSNs in improving the traditional methods of farming (ur Rehman et al., 2014, Zhao et al., 2013, Wang et al., 2006, Akyildiz et al., 2002a, Akyildiz et al., 2002b, Akyildiz and Kasimoglu, 2004, Yick et al., 2008, Ruiz-Garcia et al., 2009). The Micro-Electro-Mechanical Systems (MEMS) technology has enabled the creation of small and cheap sensors. The ubiquitous nature of operation, together with self-organized small sized nodes, scalable and cost-effective technology, enables the WSNs as a potential tool towards the goal of automation in agriculture. In this regard, precision agriculture (Chen et al., 2015, Cambra et al., 2015, Barcelo-Ordinas et al., 2013, Baseca et al., 2013, Díaz et al., 2011, López et al., 2011, Park et al., 2011, Matese et al., 2009), automated irrigation scheduling (Lichtenberg et al., 2015, Reche et al., 2015, Greenwood et al., 2010, Gutiérrez et al., 2014, Moghaddam et al., 2010), optimization of plant growth (Hwang et al., 2010), farmland monitoring (Corke et al., 2010, Voulodimos et al., 2010), greenhouse gases monitoring (Malaver et al., 2015, Yang et al., 2013, Mao et al., 2012), agricultural production process management (Díaz et al., 2011, Dong et al., 2013), and security in crops (Garcia-Sanchez et al., 2011), are a few potential applications. However, WSNs have few limitations (Akyildiz et al., 2002a, Yick et al., 2008) such as low battery power, limited computation capability and small memory of the sensor nodes. These limitations invite challenges in the design of WSN applications in agriculture.
In agriculture, most of the WSN-based applications are targeted for various applications. For example, WSNs for environmental condition monitoring with information of soil nutrients is applied for predicting crop health and production quality over time. Irrigation scheduling is predicted with WSNs by monitoring the soil moisture and weather conditions. Being scalable, the performance of an existing WSN-based application can be improved to monitor more parameters by only including additional sensor nodes to the existing architecture. The issues present in such applications are the determination of optimal deployment strategy, measurement interval, energy-efficient medium access, and routing protocols. For example, a sparse deployment of nodes with a long data collection interval is helpful for enhancing the lifetime of a network. However, challenges may emerge from the choice of the deployment region. As an example, if the field area is separated by obstructions then it will lead to attenuation of signal, thereby affecting the inter-node communication.
In the Indian scenario, the WSN-based farming solutions need to be of very low cost to be affordable by end users. However, with the increasing population, the demand of food-grain is also rising. Recent reports warns that the growth in food grain production is less than the growth in population (Shanwad et al., 2004). Also, India is one of the largest exporters of food grains, and thus, researchers (Shanwad et al., 2004, Mondal and Basu, 2009) demand to boost production by incorporating advanced technologies. Consequently, new and modern technologies are being considered in many agricultural applications to achieve the target (Mondal et al., 2004). The current state of development in the Indian scenario comprises of technologies such as WSNs, General Packet Radio Service (GPRS), Global Positioning System (GPS), remote sensing, and Geographical Information System (GIS).
In this paper, we surveyed the variants of WSNs and their potential for the advancement of various agricultural application development. We highlight the main agricultural and farming applications, and discuss the applicability of WSNs towards improved performance and productivity. We also classify the network architecture, node architecture, and communication technology standards used in agricultural applications. The real-world wireless sensor nodes and various sensors such as soil, environment, pH, and plant-health are also listed in this paper. In Section 5, we study and review the existing WSN deployments both in the global as well as the Indian scenarios. In summary, the contributions of this paper are listed as follows.
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We study the current state-of-the-art in WSNs and their applicability in agricultural and farming applications.
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The existing WSNs are analyzed with respect to communication and networking technologies, standards, and hardware.
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We analyze the prospects and problems of the existing agricultural applications with detailed case studies for global as well as the Indian scenarios.
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Finally, we present the futuristic applications highlighting the factors for improvements for the existing scenarios.
The rest of the paper is organized as follows. Section 2 presents the basics of WSNs, its requirements, potentials and different possible application in the agriculture domain. Design of a wireless sensor network for agricultural application is discussed in Section 3. The technologies and standards used in agricultural applications are analyzed in Section 4. We further discuss about the currently existing state-of-the-art and real-world applications in Section 5, and analyze the prospects and problems of the existing solutions. In Section 6, we provide few future direction of work pointing out the factors for improvement. Finally, the paper concludes in Section 7.
Section snippets
Wireless sensor networks and its potential for agricultural applications
In this section, we discuss two widely used variants of WSNs—Terrestrial Wireless Sensor Networks (TWSN) and Wireless Underground Sensor Networks (WUSN), specifically used in agricultural applications.
Network architecture for agriculture applications
In this section, we discuss the network architecture considered in various agricultural applications. We classify the architectures in various categories and highlight the potential agricultural applications suitable for each one. Fig. 3 provides a visual depiction of the architectures classified with respect to different parameters.
Based on the movement of the networked devices and nodes, we classify the existing architectures in the following categories:
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Stationary architecture: In the
Technologies and standards used in agriculture
In this section, we discuss the details of the wireless communication technologies, and the standards used in various agricultural applications. Also, we study the different wireless sensor nodes available in the market for use in these applications.
Existing real-world applications
In Section 5.1, we discuss the different categories of agricultural applications in detail, and also, bring on the real-world counterpart of the same application deployment as a case study. These applications are designed with both the TWSNs and the WUSNs. Also, we mention the developments in the Indian scenarios in Section 5.2. Although, the number of such developments is very small compared to the global scenario. In Section 5.3, we analyze the challenges, problems, and prospects of the
Future work direction
There are many potential applications of WSNs in the agriculture and farming area. The current state-of-the-art includes most works on irrigation management, vineyard production monitoring, and crop disease prediction.
Conclusion
The inclusion of WSNs is envisioned to be useful for advancing the agricultural and farming industries by introducing new dimensions. In this survey, we present a comprehensive review of the state-of-the-art in WSN deployment for advanced agricultural applications. First, we introduced the variants of WSNs—the terrestrial WSNs and underground WSNs. Then, we highlighted various applications of WSNs, and their potential to solve various farming problems. The consecutive sections of this paper
Acknowledgement
This work is supported by Information Technology Research Academy (ITRA), Government of India under ITRA-Water Grant ITRA/15(69)/WATER/M2M/01.
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