Energy Efficient IoT-Sensors Network for Smart Farming

Gupta, Zatin; Bindal, Amit Kumar; Shukla, Suruchi; Chopra, Ishveen; Tiwari, Vidhika; Srivastava, Shipra

doi:10.17762/ijritcc.v11i5.6612

Cited by 3 publications

(2 citation statements)

References 35 publications

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“…Analysis shows that this scheme can minimise the overall transmission delay and is suitable for scalable IoT networks compared to traditional delay-tolerant methods. Gupta et al (2023) created a program based on the Internet of Things that can advance smart farming. However, the farm's coverage area, location, environmental conditions, etc., can all impact the performance of IoT networks.…”

Section: Problem Statement and Contributionsmentioning

confidence: 99%

Delay-Conscious Service Quality Constraint in IoT Sensor Networks for Smart Farming

Gupta,

Bindal

2023

Journal of Computer Science

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The Internet of Things (IoT) offers different services for the agriculture industry, such as monitoring and analysing real-time data related to current weather conditions, water level, irrigation requirements, growth of plant disease and health status/temperature/humidity, etc.,). The performance of IoT networks may vary due to environmental conditions and operational areas (rural area/urban area/underwater). These constraints may degrade the transmission quality due to delay factors because the signal propagation may vary in these areas. IoT sensors are low-powered devices designed for longdistance communication. The transmission rate may be degraded due to the delay factor, which may cause packet loss/ congestion/collision, thus resulting in unnecessary re-transmission over the cost of network resources. To resolve the transmission delay issue, there is a need to develop a solution to ensure reliable transmission under the constraint of delay, and this study will introduce a delay-aware scheme to manage the uncertainty over IoT networks in rural and urban areas. Its performance will be analysed using different quality of service constraints (i.e., throughput/delay/residual Energy/Energy Consumption, etc.) using two different IoT-based communication standards, i.e., LoRaWAN and SigFox, with IoT sensor density variation from 100-400 IoT sensors only. For simulation, an NS-3 network simulator will be utilised.

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Section: Problem Statement and Contributionsmentioning

confidence: 99%

Delay-Conscious Service Quality Constraint in IoT Sensor Networks for Smart Farming

Gupta,

Bindal

2023

Journal of Computer Science

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“…Infrastructure challenges encompass issues of connectivity, power supply, and accessibility, especially in remote and rural farming areas. These challenges are discussed in the research by Ingole and Padole [22]. User acceptance challenges emphasize the importance of understanding the perspectives of farmers and stakeholders towards adopting and utilizing these technologies.…”

Section: Challenges In Iot and Ddbms Integration In Smart Agriculturementioning

confidence: 99%

Performance Analysis of Distributed Database Management System for IoT in the Context of Smart Agriculture in Indonesia

Judijanto

2023

WSNT

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The integration of Distributed Database Management Systems (DDBMS) for Internet of Things (IoT) applications in smart agriculture presents a transformative paradigm in the dynamic landscape of Indonesian agriculture. This qualitative research investigates the challenges and opportunities associated with this integration, drawing insights from interviews with diverse stakeholders, including farmers, technology developers, and policymakers. The technical challenges encompass data synchronization, network latency, and security considerations, emphasizing the need for standardized protocols and robust security measures. Infrastructure challenges, such as connectivity issues and power supply dependency, underscore the importance of rural infrastructure development. User acceptance challenges highlight resistance to change and the perceived complexity of DDBMS, emphasizing the significance of targeted awareness and training programs. Despite these challenges, stakeholders recognize the advantages of scalability, enhanced data availability, and improved decision-making capabilities offered by DDBMS. The study proposes recommendations, including technological solutions, policy interventions, and capacity-building initiatives, to address identified challenges and promote the effective utilization of DDBMS in Indonesian smart agriculture. This research contributes context-specific insights to the global discourse on IoT and DDBMS in agriculture.

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