Optimization of energy and delay on interval data based graph model of wireless sensor networks

Kavra, Radhika; Gupta, Anjana; Kansal, Sangita

doi:10.1007/s11276-023-03292-x

Cited by 5 publications

(2 citation statements)

References 44 publications

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“…The experiment that suggested the utilization of wireless sensor networks (WSN) for the purpose of automating irrigation was conducted by Kavra, Gupta, and Kansal [10]. The utilization of automatic communication for the purpose of acquiring information on soil moisture conditions in irrigation design has led to the development of wireless sensor network (WSN)based irrigation control and rescheduling, which have proven to be effective tools for enhancing water management efficiency.…”

Section: Crop Health Monitoringmentioning

confidence: 99%

An Emerging Era of Artificial Intelligence Research in Agriculture

Schaefer

2023

JRS

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According to the Food and Agriculture Organization (FAO) of the United Nations, it is projected that the global population will increase by an additional 2 billion individuals by the year 2050. However, the FAO also predicts that only a mere 4% of the Earth's total surface area will be utilized for agricultural purposes. Advancements in technology and innovative solutions to existing limitations in the agricultural sector have facilitated a notable enhancement in agricultural efficiency. The extensive utilization of machine learning and Artificial Intelligence (AI) within the agricultural industry may potentially signify a significant turning point in its historical trajectory. The utilization of AI in farming presents a range of benefits for farmers, including enhanced productivity, reduced expenses, improved crop quality, and expedited go-to-market strategies. This study aims to explore the potential applications of AI in various subsectors of the agriculture industry. This study delves into the exploration of future concepts propelled by AI, while also addressing the anticipated challenges that may arise in their applications.

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Section: Crop Health Monitoringmentioning

confidence: 99%

An Emerging Era of Artificial Intelligence Research in Agriculture

Schaefer

2023

JRS

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“…The findings indicate that within certain planar topology control schemes, it is feasible to recover from To solve the routing problem in harsh environments, a considerable amount of research has been carried out during the last decade. Kavra R et al [18] propose a planarization routing algorithm based on GG and RNG at the worst case. The findings indicate that within certain planar topology control schemes, it is feasible to recover from a failure in greedy routing without needing to switch between any adjacent faces.…”

Section: Related Workmentioning

confidence: 99%

Innovative DMHS Algorithm Application in Wireless Sensor Networks for Efficient Routing in High-Risk Environments

Ma,

Deng

2023

Sensors

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Efficient routing is essential for the proper functioning of wireless sensor networks (WSNs). Recent research has focused on optimizing energy and delay for these networks. Nevertheless, there is a dearth of studies that have examined the effects of volatile settings, such as chemical plants, coal mines, nuclear power plants, and battlefields, where connectivity is inconsistent. In such contexts, sensor networks may face security incidents, and environmental factors such as node movement and death can result in dynamic changes to the network topology. A novel design algorithm grounded on Dynamic Minimum Hop Selection (DMHS) was introduced in this paper. The key principle behind DMHS is to use a probabilistic forwarding decision-making process through a distributed route discovery strategy that utilizes dynamically adjusted minimum hop counts of nodes. Simulation results indicate that the life cycle of the DMHS algorithm increases by more than 12% over 700 nodes when compared to the traditional energy-saving algorithm. Furthermore, our algorithm performs better in the average delivery rate of node, and has a 10% to 21% improvement compared to the other algorithms. Overall, the DMHS algorithm represents an important contribution to the development of WSNs that can function robustly in high-risk and unstable environments.

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A Comprehensive Analysis on Clustering and Routing Techniques in Wireless Sensor Network

2024

2024 International Conference on Intelligent Algorithms for Computational Intelligence Systems (IACIS)

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Optimization of energy and delay on interval data based graph model of wireless sensor networks

Cited by 5 publications

References 44 publications

An Emerging Era of Artificial Intelligence Research in Agriculture

An Emerging Era of Artificial Intelligence Research in Agriculture

Innovative DMHS Algorithm Application in Wireless Sensor Networks for Efficient Routing in High-Risk Environments

A Comprehensive Analysis on Clustering and Routing Techniques in Wireless Sensor Network

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