DewBCity: blockchain network-based dew-cloud modeling for distributed and decentralized smart cities

Hati, Sourav; De, Debashis; Mukherjee, Anwesha

doi:10.1007/s11227-021-04203-7

Cited by 9 publications

(2 citation statements)

References 24 publications

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“…A developing area of research in computing science is dew computing that uses end nodes and cloud computing together to store data locally and give users access to it even when they are not online. 26,27 Agricultural fields are typically found in isolated locations in developing nations, where network access may be unavailable frequently. In this scenario, dew computing can offer local storage and enable offline access to the data.…”

Section: Related Workmentioning

confidence: 99%

Fly: Femtolet‐based edge‐cloud framework for crop yield prediction using bidirectional long short‐term memory

Dey,

Bera,

Paul

et al. 2024

Softw Pract Exp

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Crop yield prediction is a crucial area in agriculture that has a large impact on the economy of a country. This article proposes a crop yield prediction framework based on Internet of Things and edge computing. We have used a fifth generation network device referred to as femtolet as the edge device. The femtolet is a small cell base station that has high storage and high processing ability. The sensor nodes collect the soil and environmental data, and then the collected data is sent to the femtolet through the microcontrollers. The femtolet retrieves the weather‐related data from the cloud, and then processes the sensor data and weather‐related data using Bi‐LSTM. The femtolet after processing the data sends the generated results to the cloud. The user can access the results from the cloud to predict the suitable crop for his/her land. This is observed that the suggested framework provides better accuracy, precision, recall, and F1‐score compared to the state‐of‐the‐art crop yield prediction frameworks. This is also demonstrated that the use of femtolet reduces the latency by ˜25% than the conventional edge‐cloud framework.

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Section: Related Workmentioning

confidence: 99%

Fly: Femtolet‐based edge‐cloud framework for crop yield prediction using bidirectional long short‐term memory

Dey,

Bera,

Paul

et al. 2024

Softw Pract Exp

Self Cite

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“…Dew computing is an emerging research trend in cloud computing [18], [19], [20], [21]. Dew computing combines the use of end nodes such as mobile devices along with cloud computing to provide local data storage and access to the data even in offline mode.…”

Section: Related Workmentioning

confidence: 99%

E-CropReco: A Dew-Edge-based Multi-parametricCrop Recommendation Framework for Internet ofAgricultural Things

Bera¹,

Dey²,

Mukherjee³

et al. 2022

Preprint

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Crop productivity prediction and recommendation is a significant research area of smart agriculture. This paper proposes an Internet of Things (IoT) framework based on dew computing, edge computing, and federated learning, where soil parameter, weather, and climate data are analysed to predict the crop productivity of a land, and then recommend suitable crop for the land. The dew layer pre-processes and accumulates the received sensor data, and forwards to the edge server. The edge server analyses the sensor data and the climate data, and then forwards the result along with the model characteristics to the cloud for further analysis. The proposed framework is simulated in iFogSim. The theoretical analysis shows that the proposed framework has reduced the delay by 60-70% approximately and power consumption by 70-80% approximately than the conventional IoT-cloud framework. We also observe that the proposed framework has reduced the delay by 12-35% approximately and power consumption by 30-50% approximately than the edge-cloud framework. We compare four machine learning algorithms based on their performance in data analysis in terms of precision, recall, accuracy, and F-Score. We observe that each classifier obtains more than 95% prediction accuracy. An Android application is also proposed for crop recommendation.

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Green Mobile Cloud Computing forIndustry 5.0

Mukherjee¹,

Buyya

2022

Green Mobile Cloud Computing

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DewBCity: blockchain network-based dew-cloud modeling for distributed and decentralized smart cities

Cited by 9 publications

References 24 publications

Fly: Femtolet‐based edge‐cloud framework for crop yield prediction using bidirectional long short‐term memory

Fly: Femtolet‐based edge‐cloud framework for crop yield prediction using bidirectional long short‐term memory

E-CropReco: A Dew-Edge-based Multi-parametricCrop Recommendation Framework for Internet ofAgricultural Things

Green Mobile Cloud Computing forIndustry 5.0

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