IOT based Wireless Sensor Network for Precision Agriculture

Ahmad, Nisar; Hussain, Abir; Ullah, Ihsan; Zaidi, Bizzat Hussain

doi:10.1109/ieecon45304.2019.8938854

Cited by 38 publications

(15 citation statements)

References 9 publications

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“…Research on wireless sensor networks dates back to the 1980s when the United States Defense Advanced Research Projects Agency (DRPA) initiated the Distributed Sensor Network (DSN) program for the US military [20]. The distributed sensor network was anticipated to contain inexpensive cooperating nodes and achieve autonomous control [21]; however, technology was not as advanced as it was presumed to be [22].…”

Section: Wireless Sensor Networkmentioning

confidence: 99%

Blockchain-Based Wireless Sensor Networks for Malicious Node Detection: A Survey

et al. 2021

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Wireless Sensor Networks (WSNs) are broadly applied for various applications in tracking and surveillance due to their ease of use and other distinctive characteristics compelled by real-time cooperation among the sensor nodes. In WSNs, security is becoming a critical issue, as the techniques for malicious node detection adopt a one-time, centralized decision-making approach. With this paradigm, errors are difficult to avoid, and reproducibility and traceability are challenging. Hence, malicious node discovery technologies in conventional WSNs cannot assure traceability and fairness of the detection method. Herein, this paper discusses an in-depth survey of a blockchain-based approach for malicious node detection, an exhaustive examination of the integration of blockchain techniques with WSNs (BWSN), and insights into this novel concept. This survey discusses the architecture, sector-wise applications, and uses of BWSN. Moreover, this survey describes malicious node detection based on BWSN in two parts: 1) the BWSN architecture for detecting the malicious nodes and 2) the smart contract aspects in malicious node detection. Next, this survey explains the contributions of blockchain for WSN data management, which involves online information aggregation and may include auditing, event logs, and storage for information analysis and offline query processing. This survey first presents the conventional WSN solutions then the blockchain-based WSN solutions for data management. Additionally, this survey discusses the contributions of blockchain for WSN security management. It first examines the centralized WSN models for security problems, followed by a discussion of the blockchain-based WSN solutions for security management, such as offering access control, preserving information integrity, guaranteeing privacy, and ensuring WSNs' node longevity.

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Section: Wireless Sensor Networkmentioning

confidence: 99%

Blockchain-Based Wireless Sensor Networks for Malicious Node Detection: A Survey

et al. 2021

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“…Instead of using velocity vectors to manipulate these chromosomes, these chromosomes are now manipulated via the artificial genetic operators (Appendix B), that is, mutation and crossover to form new chromosomes [5]. As earlier in the PSO, the fitness of each chromosome resulting from the artificial genetic operators is calculated using the winner determination objective defined in Equation ( 4) subject to Equations ( 5)- (8). The process is repeated until the saturation point is reached.…”

Section: Proposed Algorithmsmentioning

confidence: 99%

“…Since the arrival of smart grid and the concept of smart cities, a lot has changed on the technology front [ 5 , 6 , 7 , 8 ]. A lot of work has been carried out for the architecture of IoT for smart grids to collect the information, thus enabling a lot of different fields [ 9 ].…”

Section: Introductionmentioning

confidence: 99%

Incentive Based Load Shedding Management in a Microgrid Using Combinatorial Auction with IoT Infrastructure

Zaidi

Ullah

Alam

et al. 2021

Sensors

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This paper presents a novel incentive-based load shedding management scheme within a microgrid environment equipped with the required IoT infrastructure. The proposed mechanism works on the principles of reverse combinatorial auction. We consider a region of multiple consumers who are willing to curtail their load in the peak hours in order to gain some incentives later. Using the properties of combinatorial auctions, the participants can bid in packages or combinations in order to maximize their and overall social welfare of the system. The winner determination problem of the proposed combinatorial auction, determined using particle swarm optimization algorithm and hybrid genetic algorithm, is also presented in this paper. The performance evaluation and stability test of the proposed scheme are simulated using MATLAB and presented in this paper. The results indicate that combinatorial auctions are an excellent choice for load shedding management where a maximum of 50 users participate.

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“…summarizes the applications of WSN for monitoring environmental factors in precision agriculture. Ahmad et al 9 presented the smart monitoring system based on different parameters for sensing the environmental factors. The sensors include air quality, ultraviolet (UV) index, soil moisture, relative humidity and temperature sensors.…”

Section: Environmental Factors In Precision Agriculturementioning

confidence: 99%

Bio-inspired cluster–based optimal target identification using multiple unmanned aerial vehicles in smart precision agriculture

Salam

Javaid

Ahmad

2021

International Journal of Distributed Sensor Networks

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Farming is the major profession in several republics for centuries. However, due to the immigration of individuals from rural to urban, there is prevention in farming. The use of modern technology in the precision agriculture field increases productivity and also improves the exports of a country. The productivity may suffer due to different environmental factors, diseases and insects attacks on the crops, especially tomatoes. The target area (i.e. the affected crops area due to environmental factors) identification and delivery of timely information about diseases in the crops to the ground station are mandatory to make the precautionary measurements. In flying sensor networks, the localization and clustering of multiple unmanned aerial vehicles for target areas identification is a challenging task due to energy constraints, communication range, frequent change in topology, link expiration and high mobility. In this article, we proposed the localization and clustering of multiple unmanned aerial vehicles for the identification of affected target areas in the tomato crop field. The localization of unmanned aerial vehicles depends on the weights of environmental factors, that is, relative humidity, soil moisture, temperature, light intensity, NPK (nitrogen (n), phosphorus (p) and potassium (k)) and power of hydrogen (pH). A honey bee optimization approach is used for the localization and formation of multiple unmanned aerial vehicles’ cluster to accurately identify the target areas. The performance of our bio-inspired approach is compared in terms of communication overhead, packet delivery ratio, mean end-to-end delay and energy consumption with the existing swarm intelligence–based schemes and validated via a simulation. The simulation result shows that the bio-inspired approach performs better among the selected approaches.

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IOT based Wireless Sensor Network for Precision Agriculture

Cited by 38 publications

References 9 publications

Blockchain-Based Wireless Sensor Networks for Malicious Node Detection: A Survey

Blockchain-Based Wireless Sensor Networks for Malicious Node Detection: A Survey

Incentive Based Load Shedding Management in a Microgrid Using Combinatorial Auction with IoT Infrastructure

Bio-inspired cluster–based optimal target identification using multiple unmanned aerial vehicles in smart precision agriculture

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