Leveraging the Internet of Things (IoT) Paradigm Towards Smarter Applications

Neeba, E. A.; Aswini, J.; Priyadarshini, Rojalina

doi:10.4018/978-1-5225-9023-1.ch017

Cited by 2 publications

(4 citation statements)

References 11 publications

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“…Doctors should be able to view a patient's cancer data at any time and from any location over the internet. Moreover, the big data and real‐time processing in the healthcare field were presented using various novel techniques of data mining algorithms such as ant colony optimization, simulated annealing (SA), and artificial neural network with artificial intelligence (AI) 7,9‐12 …”

Section: Introductionmentioning

confidence: 99%

“…Moreover, the big data and real-time processing in the healthcare field were presented using various novel techniques of data mining algorithms such as ant colony optimization, simulated annealing (SA), and artificial neural network with artificial intelligence (AI). 7,[9][10][11][12] This article presents an artificial hummingbird (AHB) algorithm-based convolutional neural network (AHB-CNN) model for predicting the abnormality in cancer patients' health signals derived from the IoT sensors. The IoT-based healthcare framework is utilized to offer healthcare services to patients via the mobile platform.…”

Section: Introductionmentioning

confidence: 99%

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A secure IoT based healthcare framework using modified RSA algorithm using an artificial hummingbird based CNN

Jacob

Pravin

Kumar

2022

Trans Emerging Tel Tech

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Recently, a wide variety of real‐world problems are solved via cloud computing, deep learning, machine learning, artificial intelligence, and the Internet of Things (IoT). These methodologies are concerned with different areas like smart cities, agriculture, transportation systems, and healthcare systems. The existing researchers focused on the health care monitoring application along with IoT and cloud computing. It met several shortcomings in case of computational complexity, cost, time, and improper health care data storage and so forth. To overcome these challenges, the novel IoT‐enabled secure healthcare monitoring model is proposed in this study. At first, several sensors are deployed in the human body thereby collecting patients' data with respect to vital parameters like body temperature deviation. The patient's health record dataset consists of 10 attributes namely phone numbers, marital status, address, age, name, heartbeat rate, oxygen level, smoking, temperature, and blood pressure. The data size reduction and normalization are performed in the IoT medical sensor dataset which contains the redundant or irrelevant attributes that are eliminated during pre‐processing. The artificial hummingbird (AHB) algorithm‐based convolutional neural network (AHB‐CNN) model performs both feature extraction and classification of cancer disease. The AHB‐CNN model classifies whether the patient is prone to cancer or not based on the sensor input collected. The received results are then sent to the hospital management for analysis. The Rivest‐Shamir‐Adleman (RSA) encryption method is mostly used in this study due to the major benefits it gives in terms of asymmetric encryption, ease of use, simpler deployment, and high security associated with factoring large prime numbers. A modified RSA algorithm is used in this article which uses the double encryption‐decryption process and “n” prime numbers to enhance the security of the conventional RSA algorithm. The data is always encrypted during transit before being stored in the cloud or for further processing. Depending upon the experimental consequences, the proposed method established superior performances compared to other state‐of‐art techniques.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

A secure IoT based healthcare framework using modified RSA algorithm using an artificial hummingbird based CNN

Jacob

Pravin

Kumar

2022

Trans Emerging Tel Tech

View full text Add to dashboard Cite

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“…4 Currently, smartphones, laptops and other handheld devices use WSN for transferring and observing data. [5][6][7][8][9][10] This device contains diverse specifications to process data and maintains the record regarding temperature, health details of the patients as well as earthquake records. 11 On the other hand, the working of WSN is influenced by means of communication protocol and the network lifetime can be enhanced by minimizing the energy consumption.…”

Section: Introductionmentioning

confidence: 99%

“…Currently, smartphones, laptops and other handheld devices use WSN for transferring and observing data 5‐10 . This device contains diverse specifications to process data and maintains the record regarding temperature, health details of the patients as well as earthquake records 11 .…”

Section: Introductionmentioning

confidence: 99%

Multi‐objective moth swarm based sailfish model for optimal routing in wireless sensor network

Gunasekar

Natesan²,

Samiayya

2022

Concurrency and Computation

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In recent years, the WSN are emerging swiftly since it finds applications in various domains including weather monitoring, attack detection, industrial monitoring, monitoring of submarine organisms, patient monitoring as well as the monitoring of ecological disorders. But WSN is also influenced by various other factors like network lifetime and energy consumption. It is necessary to provide an energy effective protocol to conquer certain troubles that includes packet delivery ratio, network lifetime, residual energy as well as effective routing in WSN. Therefore, this article aims to propose a novel protocol to enhance the energy efficiency of the network thereby providing an optimal routing path. This can be achieved by selecting an optimal cluster head that maintains communication between the base station and the sensor node. In this article, a novel multi-objective moth swarm based sailfish (MOMS-SF) technique is employed in selecting an optimal cluster head. The proposed MOMS-SF technique enhances the network lifetime and minimizes the energy consumption of the network. Finally, the evaluation results are conducted to determine the network performances of the proposed MOMS-SF approach. Also, a comparative analysis is carried out and the graphical analyzes for various parameters are made for various approaches to determine the effectiveness of the proposed system.

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Leveraging the Internet of Things (IoT) Paradigm Towards Smarter Applications

Cited by 2 publications

References 11 publications

A secure IoT based healthcare framework using modified RSA algorithm using an artificial hummingbird based CNN

A secure IoT based healthcare framework using modified RSA algorithm using an artificial hummingbird based CNN

Multi‐objective moth swarm based sailfish model for optimal routing in wireless sensor network

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