Intelligent Boundary Determination of Oil Spill Detection Using IOT

Abhijith, H; Raj, S. Deepak; Babu, Hari

doi:10.2139/ssrn.3167315

Cited by 3 publications

(2 citation statements)

References 15 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Oil Spill detection is a remote IoT application, which uses resource constrained networks [22]. It includes deployment of many low cost, low power sensing nodes which has capabilities to sense, process and communicate the data.…”

Section: Introductionmentioning

confidence: 99%

Secure Data Transmission Framework for Internet of Things based on Oil Spill Detection Application

Abhijith¹,

Rameshbabu²

2021

IJACSA

View full text Add to dashboard Cite

Internet of Things (IoT) is a leading technology which can interlink anything to Internet and makes everything to intelligent and smart. IoT is not just a single technology. IoT is a combination of various technologies like communication, data analytics, sensors and actuators, cloud computing, artificial intelligence, machine learning, etc. Applications of IoT are spread across various domains. IoT is most suitable for remote applications like underwater networks. One such application is oil spill detection in ocean. Oil spill in an ocean is a critical challenge that causes damages to marine ecosystem. Detection of oil spills in a real time manner helps to resolve the problem quickly to minimize the damage. IoT can be used to detect the oil spill by making use of sensors deployed at various locations of ocean. With a massive amount of sensors deployed and the huge amount of data associated with it, there remain concerns about the data management. Also amount of data generated in IoT based remote sensing network is usually enormous for the servers to process and many times data generated are redundant. Hence there is a need for designing a framework which addresses both aggregation of data and security related issues at various aggregation points. In this paper we are proposing a secure data transmission framework for detecting oil spill through IoT, which avoids redundant data transmission through data aggregation and ensures secure data transmission through authentication and light weight encryption.

show abstract

Section: Introductionmentioning

confidence: 99%

Secure Data Transmission Framework for Internet of Things based on Oil Spill Detection Application

Abhijith¹,

Rameshbabu²

2021

IJACSA

View full text Add to dashboard Cite

show abstract

“…The reduction of redundant data is not that significant through normal data aggregation techniques. Hence there is a need for adding some intelligence to nodes to decide whether to transmit the data or not [16]. In the constrained remote IoT applications where we have limited resources, communication consumes more energy than compared to processing.…”

Section: Introductionmentioning

confidence: 99%

Intelligent Data Aggregation Framework for Resource Constrained Remote Internet of Things Applications

Abhijith¹,

Babu²

2021

IJACSA

View full text Add to dashboard Cite

Internet of Things (IoT) is a technology that can connect everything to the Internet. IoT can be used in a wide range of applications which includes remote applications like Underwater networks. Remote applications involve the deployment of several low-power, low-cost interconnected sensor nodes in the specific region. With a massive amount of devices connected to the IoT and the considerable amount of data associated with it, there remain concerns about data management. Also, the amount of data generated in an extensive IoT-based remote sensing network is usually enormous for the servers to process, and many times data generated are redundant. Hence there is a need for designing a framework that addresses both aggregations of data and security-related issues at various aggregation points. In this paper, we are proposing an intelligent data aggregation mechanism for IoT-based remote sensing networks. This method avoids redundant data transmission by adapting spatial aggregation techniques. The proposed method was tested through simulations, and the results prove the efficiency of the proposed work.

show abstract