Physiological Monitoring by Fail Proof Lifetime Enhancement Algorithm for Smart Digital Environments

• Published in: ACM transactions on multimedia computing communications and applications 2020-05, Article 3381087
• Main Authors: S, Malathy, Mallikarjuna, Basetty, R, Maheswar, GR, Kanagachidambaresan, TVP, Sundararajan, A, Sampathkumar, Dhasarathan, Vigneswaran
• Format: Article
• Language: English
• ISSN: 1551-6857; 1551-6865
• DOI: 10.1145/3381087

Abstract only Physiological signals monitoring in smart digital environment became ease with miniaturized embedded systems. The node loses its energy due to continuous monitoring and becomes unavailable during critical conditions. The implanted node dissipated heat and causes tissue damage when overloaded. The problem is addressed through Fail Proof Lifetime Enhancement (FPLE) Algorithm by optimally scheduling the nodes in digital environment based on the energy level and through Threshold T* policy model proposed. The objective is achieved by classifying packets based on their status and packets are transmitted towards sink once it meets a threshold value T*. A part of the energy in the sensor node is utilized during emergencies to ensure the availability of monitoring the subject during critical conditions. The subject status is realized as a Finite State Machine and evaluated through the Markov model and threshold T* based framework is adopted to enhance the lifetime of the network. The FPLE algorithm performs better than the SingleHop, MultiHop and ATTEMPT routing scheme in terms of network lifetime and throughput. The proposed FPLE algorithm provides 1.91 times lifetime and 1.1 times throughput when compared with the ATTEMPT communication protocol. The false data generation is identified and alarmed through this approach, and the FPLE algorithm also ensures monitoring during critical conditions. The implanted node is loaded least to avoid thermal dissipation and tissue damage of the subject. The FPLE algorithm is tested in real-time digital environment for its novel working, provides better results when compared to ATTEMPT, SingleHop, and MultiHop protocol.