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- 검색키워드
- 저자 : Jhanjhi N. Z. (검색결과 3 건)
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The Smart Medicine Delivery Using UAV for Elderly Center
Li, Jie,Weiwei, Goh,N.Z., Jhanjhi,David, Asirvatham International Journal of Computer ScienceNetwork S 2023 International journal of computer science and netw Vol.23 No.1
Medication safety and medicine delivery challenge the well-being of the elderly and the management of the elderly center. With the outbreak of COVID-19, the elderly in the care center were challenged by the inconvenience of the medication restocking. The purpose of this paper accentuates the importance of the design and development of an UAV-based Smart Medicine Case (UAV-SMC) to improve the performance of medication management and medicine delivery in the elderly center. The researchers came up with the design of UAV-SMC in the light of the UAV and IoT technology to improve the performance of both Medication Practice Management (MPM) and Low Inventory Detection and Delivery (LIDD). Based on the result, with UAV-SMC, the performance of both MPM and LIDD was significantly improved. The UAV-SMC improves the efficacy of medication management in the elderly center by 26.97 to 149.83 seconds for each medication practice and 9.03 mins for each time of medicine delivery in Subang Jaya Malaysia. This paper only investigates the adoption of UAV-SMC in the content of elderly center rather than other industries. The authors consider integrating the UAV-SMC with the e-pharmacy system in the future. In conclusion, the UAV-SMC has significantly improved the medication management and guard the safety of elderly and caretaker in the elderly in the post-pandemic times.
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Bargaining based Design Mechanism for delay sensitive tasks of mobile crowdsensing in IoT
Ahmad Waqas,Ullah Ata,Sheharyar,Jhanjhi N.Z.,Ghoniem Rania M.,Brohi Sarfraz Nawaz 한국통신학회 2024 ICT Express Vol.10 No.1
Internet of Things (IoT) is getting growing interest to offer great opportunities in combination with Mobile Crowd Sensing for real-time applications. Existing approaches motivate mobile workers (MWs) for approaching the distant locations to receive attractive incentives for traveling. The main question addressed is that a number of tasks remain incomplete out of total al-located tasks. Moreover, the profitability and feasible budget constraints of the platform is also not considered. This paper presents Bargaining based Design Mechanism (BDM) to involve the nearest located MWs to improve the completion of tasks. The main method involves a bargaining based game model that increases the task completion ratio while considering the feasible budget constraint, platform profitability and social welfare. The proposed approach comprises of two algorithms: one for the selection of optimal MWs with low cost and less delay. Second is to organize bargaining for rewarding the platform on social welfare. Our work is validated by developing a testbed on Windows Azure cloud. Results prove that proposed BDM out-performs the counterparts in terms of decay coefficient, task completion ratio, participant’s winning ratio, fraction of task incompletion and social welfare.
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A Novel SDN-Based Security Framework for Wireless Sensor Networks Using TDCNN and PGF-ECCMohit
Kumar,Mukherjee Priya,Verma Sahil,Kavita,Jhanjhi N. Z.,Vimal S.,Almutain Bandar 한국컴퓨터산업협회 2023 Human-centric Computing and Information Sciences Vol.13 No.-
Wireless sensor networks (WSN) comprise a huge number of stationary or mobile sensor nodes that considerably support multi-hop communication. Intruder attacks such as wormholes, spoofing, etc., make it more susceptible in turn influence WSN’s confidentiality. Therefore, utilizing tanh activation function centered deep convolution neural network (TDCNN) and polynomial Galois field elliptical curve cryptography (PGF-ECC), a novel approach named malicious node detection and privacy preservation of software-defined WSN is conceptualized in this work. Many measures have been taken in the work for assuring security. Utilizing taxicab metric centered KMedoid (TM-KMedoid) algorithm, the sensor nodes of the network are initially sorted into clusters. After that, using the Horse optimization algorithm (HOA), the cluster head (CH) selection is performed where the best node in the cluster is selected as the CH. Next, the data packets are transferred by the CH to the base station (BS) via the software-defined networking (SDN) controller. The SDN controller is applied with a TDCNN classifier that predicts the node’s trustworthiness for detecting whether the node is malicious or not. The data is transferred to BS if the node is a trusted one else, the node gets rejected. The PGF-ECC algorithm is employed for ensuring the data’s secure transmission to the BS. The proposed method’s performance is contrasted with the existent systems in an experimental evaluation. It exhibits superior performance when analogized to top-notch techniques, and highly assures the network’s authenticity.
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