LCIPA: Lightweight clustering protocol for industry 4.0 enabled precision agriculture

Mahajan, Hemant B.; Junnarkar, Aparna A.; Tiwari, Mohit; Tiwari, Tripti; Upadhyaya, Makarand

doi:10.1016/j.micpro.2022.104633

Cited by 38 publications

(6 citation statements)

References 28 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…The simulation findings show that the LCIPA protocol is more efficient than the base techniques. The created method, however, is complicated and unable to repair database problems [18].…”

Section: Related Workmentioning

confidence: 99%

Energy efficient cluster head using modified fuzzy logic with WOA and path selection using Enhanced CSO in IoT-enabled smart agriculture systems

Rai

Rajasekaran

2023

Preprint

View full text Add to dashboard Cite

The advent of Internet of Things (IoT) in agriculture has revolutionized the way farmers monitor and manage their crops. IoT-enabled sensors can provide real-time data on various environmental parameters such as temperature, humidity, soil moisture, and crop growth, which can be used to make informed decisions and optimize crop yield. However, the vast amount of data generated by these sensors poses a significant challenge in terms of data processing and communication. To address this challenge, clustering is often used to group the sensors into clusters and elect a Cluster Head (CH) to communicate with the gateway node. The selection of an appropriate CH and the optimal path for data transmission are critical factors that affect the performance of the IoT system. In this paper, we propose a novel approach to optimize the CH selection and path selection using modified Fuzzy Logic, Whale optimization algorithm (WOA) and Enhanced Crow Swarm Optimization (ECSO). Fuzzy Logic is used to evaluate the relevant parameters such as energy, distance, overhead, trust, and node degree to select the most suitable CH. ECSO is then employed to find the optimal path for data transmission based on the selected CH. We evaluate the proposed approach using simulation experiments in a smart agriculture scenario. The results show that our approach outperforms existing approaches in terms of throughput, packet delivery ratio, delay, and energy efficiency. Our proposed approach can significantly improve the performance of IoT-enabled smart agriculture systems, leading to better crop yield and higher profitability for farmers. The results of our simulation experiments demonstrate the superiority of our approach over existing one’s throughput, Packet Delivery Ratio (PDR), delay, energy consumption efficiency is found in the result section.

show abstract

“…The simulation findings show that the LCIPA protocol is more efficient than the base techniques. The created method, however, is complicated and unable to repair database problems [18].…”

Section: Related Workmentioning

confidence: 99%

Energy efficient cluster head using modified fuzzy logic with WOA and path selection using Enhanced CSO in IoT-enabled smart agriculture systems

Rai

Rajasekaran

2023

Preprint

View full text Add to dashboard Cite

show abstract

“…The topics of Agriculture-Industry 4.0 (I4) [ 1 , 2 , 3 , 4 , 5 , 6 , 7 , 8 , 9 , 10 , 11 , 12 , 13 , 14 , 15 , 16 , 17 , 18 , 19 , 20 , 21 ] and Foods-I4 [ 22 , 23 , 24 , 25 , 26 , 27 , 28 , 29 , 30 , 31 , 32 , 33 , 34 , 35 , 36 , 37 , 38 , 39 , 40 , 41 , 42 , 43 , 44 , 45 , 46 , 47 , 48 , 49 , 50 , 51 , 52 , 53 , 54 , 55 , 56 , 57 , 58 , 59 ,…”

Section: Introductionunclassified

“…First, food comes from agriculture. Studies and talks on deploying I4 in agriculture to increase food security for the growing population have been well reported [ 1 , 2 , 3 , 4 , 5 , 6 , 7 , 8 , 9 , 10 , 11 , 12 , 13 , 14 , 15 , 16 , 17 , 18 , 19 , 20 , 21 ]. That was a smart move.…”

Section: Introductionmentioning

confidence: 99%

“…Second, I4 and related technologies might make food agriculture firms more competitive in the digital age [ 4 ]. Agriculture 4.0 is typified by the growing use of digital technology in food [ 5 ].…”

Section: Introductionmentioning

confidence: 99%

“…The fundamental question is how IoT will assist food and agriculture. I4 smart agriculture uses IoT in urban and rural areas [ 4 ].…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

A Conceptual Model Relationship between Industry 4.0—Food-Agriculture Nexus and Agroecosystem: A Literature Review and Knowledge Gaps

Yap,

Al-Mutairi

2024

Foods

View full text Add to dashboard Cite

With the expected colonization of human daily life by artificial intelligence, including in industry productivity, the deployment of Industry 4.0 (I4) in the food agriculture industry (FAI) is expected to revolutionize and galvanize food production to increase the efficiency of the industry’s production and to match, in tandem, a country’s gross domestic productivity. Based on a literature review, there have been almost no direct relationships between the I4—Food-Agriculture (I4FA) Nexus and the agroecosystem. This study aimed to evaluate the state-of-the-art relationships between the I4FA Nexus and the agroecosystem and to discuss the challenges in the sustainable FAI that can be assisted by the I4 technologies. This objective was fulfilled by (a) reviewing all the relevant publications and (b) drawing a conceptual relationship between the I4FA Nexus and the agroecosystem, in which the I4FA Nexus is categorized into socio-economic and environmental (SEE) perspectives. Four points are highlighted in the present review. First, I4 technology is projected to grow in the agricultural and food sectors today and in the future. Second, food agriculture output may benefit from I4 by considering the SEE benefits. Third, implementing I4 is a challenging journey for the sustainable FAI, especially for the small to medium enterprises (SMEs). Fourth, environmental, social, and governance (ESG) principles can help to manage I4’s implementation in agriculture and food. The advantages of I4 deployment include (a) social benefits like increased occupational safety, workers’ health, and food quality, security, and safety; (b) economic benefits, like using sensors to reduce agricultural food production costs, and the food supply chain; and (c) environmental benefits like reducing chemical leaching and fertilizer use. However, more studies are needed to address social adaptability, trust, privacy, and economic income uncertainty, especially in SMEs or in businesses or nations with lower resources; this will require time for adaptation to make the transition away from human ecology. For agriculture to be ESG-sustainable, the deployment of I4FA could be an answer with the support of an open-minded dialogue platform with ESG-minded leaders to complement sustainable agroecosystems on a global scale.

show abstract

Social context-aware and fuzzy preference temporal graph for personalized B2B marketing campaigns recommendations

et al. 2023

View full text Add to dashboard Cite

LCIPA: Lightweight clustering protocol for industry 4.0 enabled precision agriculture

Cited by 38 publications

References 28 publications

Energy efficient cluster head using modified fuzzy logic with WOA and path selection using Enhanced CSO in IoT-enabled smart agriculture systems

Energy efficient cluster head using modified fuzzy logic with WOA and path selection using Enhanced CSO in IoT-enabled smart agriculture systems

A Conceptual Model Relationship between Industry 4.0—Food-Agriculture Nexus and Agroecosystem: A Literature Review and Knowledge Gaps

Social context-aware and fuzzy preference temporal graph for personalized B2B marketing campaigns recommendations

Contact Info

Product

Resources

About