Fuzzy Logic based Smart Irrigation System using Internet of Things

Krishnan, R. Santhana; Julie, E. Golden; Robinson, Y. Harold; Raja, S.; Kumar, Raghvendra; Thong, Pham Huy; Sơn, Lê Hoàng

doi:10.1016/j.jclepro.2019.119902

Cited by 161 publications

(61 citation statements)

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“…The system can schedule irrigation employing soil moisture content, temperature, and humidity. This system can provide acknowledgment messages of the job's statuses via mobile phone [13]. Although numerous researches have presented the irrigation scheduling based on a soilbased approach, the irrigation scheduling using solely soil-based approach may fail to deliver enough amounts of water to plants as reported in [14], resulting in severe water stress of the plant.…”

Section: Introductionmentioning

confidence: 99%

An Intelligent Irrigation Scheduling System Using Low-Cost Wireless Sensor Network Toward Sustainable and Precision Agriculture

et al. 2020

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Agricultural irrigation developments have gained attention to improve crop yields and reduce water use. However, traditional irrigation requires excessive amounts of water and consumes high electrical energy to schedule irrigations. This paper proposes a fuzzy-based intelligent irrigation scheduling system using a low-cost wireless sensor network (WSN). The fuzzy logic system takes crop and soil water variabilities into account to adaptively schedule irrigations. The theoretical crop water stress index (CWSI) is calculated to indicate plant water status using canopy temperature, solar irradiation, and vapor pressure deficit. Furthermore, the soil moisture content obtained by a capacitive soil moisture sensor is used as a determination of water status in soil. These two variables are thus incorporated to improve the precision of the irrigation scheduling system. In the experiment, the proposed irrigation scheduling system is validated and compared with existing conventional irrigation systems to explore its performance. Implementation of this system leads to a decrease in water use by 59.61% and electrical energy consumption by 67.35%, while the crop yield increases by 22.58%. The experimental results reveal that the proposed irrigation scheduling system is effective in terms of precision irrigation scheduling and efficient regarding water use and energy consumption. Finally, the cost analysis is performed to confirm the economic benefit of the proposed irrigation scheduling system. INDEX TERMS Crop water stress index (CWSI), Fuzzy logic system, Irrigation scheduling, Wireless sensor network (WSN), Soil moisture content.

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Section: Introductionmentioning

confidence: 99%

An Intelligent Irrigation Scheduling System Using Low-Cost Wireless Sensor Network Toward Sustainable and Precision Agriculture

et al. 2020

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“…For the study, both the physiological and agronomic properties were taken into consideration while experimentation. R. Santhana Krishnan et al [102], designed an automated irrigation method. The authors developed a fuzzy logic-based system for precision irrigation by using Global System for Mobile Communication (GSM) service to enable farmers to water the fields.…”

Section: B Iot In Irrigationmentioning

confidence: 99%

Recent Developments of the Internet of Things in Agriculture: A Survey

2020

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A rise in the population has immensely increased the pressure on the agriculture sector. With the advent of technology, this decade is witnessing a shift from conventional approaches to the most advanced ones. The Internet of Things (IoT) has transformed both the quality and quantity of the agriculture sector. Hybridization of species along with the real-time monitoring of the farms paved a way for resource optimization. Scientists, research institutions, academicians, and most nations across the globe are moving towards the practice and execution of collaborative projects to explore the horizon of this field for serving mankind. The tech industry is racing to provide more optimal solutions. Inclusion of IoT, along with cloud computing, big data analytics, and wireless sensor networks can provide sufficient scope to predict, process, and analyze the situations and improve the activities in the real-time scenario. The concept of heterogeneity and interoperability of the devices by providing flexible, scalable, and durable methods, models are also opening new domains in this field. Therefore, this paper contributes towards the recent IoT technologies in the agriculture sector, along with the development of hardware and software systems. The public and private sector projects and startup's started all over the globe to provide smart and sustainable solutions in precision agriculture are also discussed. The current scenario, applications, research potential, limitations, and future aspects are briefly discussed. Based on the concepts of IoT a precision farming framework is also proposed in this article.

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“…As such, the FLS has been widely adopted in research on small devices and especially IoTs. For instance, the FLS has been applied to node selection [22] and the development of IoTs in irrigation systems [23].…”

Section: Introductionmentioning

confidence: 99%

An Enhanced CoAP Scheme Using Fuzzy Logic With Adaptive Timeout for IoT Congestion Control

2021

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Congestion management in the Internet of Things (IoT) is one of the most challenging tasks in improving the quality of service (QoS) of a network. This is largely because modern wireless networks can consist of an immense number of connections. Consequently, limited network resources can be consumed simultaneously. This eventually causes congestion that has adverse impacts on both throughput and transmission delay. This is particularly true in a network whose transmissions are regulated by the Constrained Application Protocol (CoAP), which has been widely adopted in the IoT network. CoAP has a mechanism that allows connection-oriented communication by means of acknowledgment messages (ACKs) and retransmission timeouts (RTOs). However, during congestion, a client node is unable to efficiently specify the RTO, resulting in unnecessary retransmission. This overhead in turn causes even more extensive congestion in the network. Therefore, this research proposes a novel scheme for optimally setting the initial RTO and adjusting the RTO backoff that considers current network utilization. The scheme consists of three main components: 1) a multidimensional congestion estimator that determines congestion conditions in various aspects, 2) precise initial RTO estimation by means of a relative strength indicator and trend analysis, and 3) a flexible and congestion-aware backoff strategy based on an adaptive-boundary backoff factor evaluated by using a fuzzy logic system (FLS). The simulation results presented here reveal that the proposed scheme outperforms state-of-the-art methods in terms of the carried load, delay and percentage of retransmission.

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Fuzzy Logic based Smart Irrigation System using Internet of Things

Cited by 161 publications

References 50 publications

An Intelligent Irrigation Scheduling System Using Low-Cost Wireless Sensor Network Toward Sustainable and Precision Agriculture

An Intelligent Irrigation Scheduling System Using Low-Cost Wireless Sensor Network Toward Sustainable and Precision Agriculture

Recent Developments of the Internet of Things in Agriculture: A Survey

An Enhanced CoAP Scheme Using Fuzzy Logic With Adaptive Timeout for IoT Congestion Control

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