Faculty Publications
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Item Multimetrics-based objective function for low-power and lossy networks under mobility(Springer Verlag service@springer.de, 2019) Sanshi, S.; Jaidhar, C.D.Due to the popularity of Low-power and Lossy Networks (LLN), numerous low-power device applications are emerging and driving the need for an efficient routing protocol. Recently, the Internet Engineering Task Force (IETF) standardized the IPv6 Routing Protocol for Low-power and Lossy Networks (RPL). To route the packets, the RPL constructed a Directed Acyclic Graph (DAG) rooted towards the DAG root using the Objective Function (OF). However, the OF supported by the standard RPL did not yield better performance, since it used a single metric. Therefore, an OF based on Multimetrics (MMOF), which combines multiple routing metrics for Static Router Nodes (SRNs) and Mobile Nodes (MNs), has been proposed in this work. From the simulation results, it was observed that the proposed MMOF showed better performance compared with other existing OFs of the RPL. © Springer Nature Singapore Pte Ltd. 2019Item A comprehensive security framework for WBANs in the healthcare environment(CRC Press, 2024) Pabitha, B.; Sanshi, S.; Karthik, N.The emergence of technology is constantly required by human society's healthcare system, where a patient is added to the environment of sickness every day. By providing real-time monitoring of patient vital signs, enabling remote patient care, and enhancing general medical diagnostics, Wireless Body Area Networks (WBANs) in e-healthcare have revolutionized the healthcare business. In our fast-paced environment, it is impossible to monitor every patient individually. Instead, WBAN can be used to treat patients in life-threatening situations. A new wireless network called WBAN was created using many tiny, short-power sensor nodes, communication links between nearby nodes, and a central base station to store and analyze the data. WBAN uses low-power, low-cost hardware with a 10 Kbps to 10 Mbps data rate. Many industries, including healthcare, senior care, sports and fitness, chronic illness management, military and emergency services, innovative apparel and fashion, precision agriculture, and farming, can successfully implement WBAN. These WBANs can be made using wearable digital apparel, accessories, and other items. In this chapter, WBAN is used in the healthcare system to monitor the fundamental values of temperature, pressure, blood sugar, and other parameters using a larger number of sensor nodes, transmit the monitored information promptly to a nearby base station (server), and then conduct data analysis to determine the patient's status accurately. As a result, tracking nodes and data transfer protocols must be highly secure to ensure data integrity. Here, strategies for potential node failures, improved technology for data connection faults, and corrective measures are provided to ensure confidentiality, integrity, and availability (CIA) for accurate analysis of patient data collection. However, there are significant privacy and data security issues that have been brought up by the use of WBANs in healthcare settings. This chapter offers a thorough security framework to handle the particular problems WBANs in e-healthcare provide. To guarantee the confidentiality, integrity, and accessibility of sensitive patient data, the framework includes encryption, authentication, access control, and intrusion detection technologies. Adopting contemporary security measures will lead to better patient outcomes and a more robust and secure healthcare ecosystem, promoting confidence between patients, healthcare providers, and technology. © 2025 selection and editorial matter, Anuj Kumar Singh and Sachin Kumar. All rights reserved.Item Assessment of objective functions under mobility in RPL(Springer Verlag, 2018) Sanshi, S.; Jaidhar, J.Due to the technological advancement in Low-power and Lossy Network (LLN), the sensor node mobility has become a basic requirement. Routing protocol designed for LLN must ensure certain requirements in a mobile environment such as reliability, flexibility, scalability to name a few. To meet the needs of LLN, Internet Engineering Task Force (IETF) released the standard IPv6 Routing Protocol for LLNs (RPL). RPL depends on Objective Function (OF) to select optimized routes from source to destination. However, the standard did not specify which OF to use. In this study, performance analysis of different OFs such as Objective Function zero (OF0), Energy-based Objective Function (OFE), Delay-Efficient Objective Function (OFDE), and Minimum Rank with Hysteresis Objective Function (MRHOF) is carried out under different mobility models, which makes this study unique. The metrics used to measure the performance are latency, packet delivery ratio (PDR), and power consumption. Simulation results demonstrate that under different mobility models, MRHOF achieved better results in terms of PDR and power consumption, while OFDE shows better results in terms of latency compared to other OFs. © Springer Nature Singapore Pte Ltd. 2018.Item Mobility aware routing protocol based on DIO message for low power and lossy networks(Springer Verlag service@springer.de, 2020) Sanshi, S.; Jaidhar, C.D.Mobility support has become a crucial requirement for many of the Low power and Lossy Networks applications, and designing an efficient mobility aware routing protocol towards this end has become an important research topic. In this paper, a Mobility Aware Routing Protocol for Low power and Lossy Networks (MARPL) that updates the Preferred Parent Node information soon after it receives the DIO message has been proposed. In the proposed approach, the Mobile Node is aware of its mobility and updates the PPN information without waiting for the route expiration time. To measure the effectiveness of the proposed MARPL, simulation works were carried out on a Contiki-based Cooja simulator for different mobility models. The obtained simulation results showed that the proposed MARPL performed better compared with the standard RPL for healthcare applications. © Springer Nature Switzerland AG 2020.Item Cardiovascular Diseases Divination using Artificial Neural Network with Ensemble Models(Institute of Electrical and Electronics Engineers Inc., 2023) Pabitha, B.; Sanshi, S.; Karthik, N.Health is wealth, but nowadays, wealth is health, where humans keep running their day-to-day activities without caring about their health for various reasons. Every human being in this world suffers from one or other diseases. Recently, cardiovascular diseases like heart attacks are prevalent in all age groups. Addressing cardiovascular diseases is essential before the disease reaches a crucial stage. Nowadays, artificial intelligence algorithms have been used to detect diseases in their early stages. In this piece of writing, a model of an artificial neural network is utilised to analyze, detect and predict the likelihood of cardiovascular disease in the early stages. In this proposed work, feed forward propagation, forward the input data to learn and map the relationships between inputs and outputs, and backward propagation is used to reduce the errors in the data. Further, an ensemble learning stacked model is used to achieve high accuracy in the prediction of diseases. To verify the correctness of the model, ensemble learning to stack is executed with three different models, namely Model 1, Model 2, and Model 3, with varying sets of feature selections. The experiment results show an accuracy rate of 93% in their predictions. © 2023 IEEE.Item Spatial Dynamics for Identification of Individuals through Gait and Other Locomotion Activities(Institute of Electrical and Electronics Engineers Inc., 2024) Anusha, R.; Sanshi, S.Gait, the pattern of walking, has been extensively studied and various methods have been developed to use it as a biometric for individual recognition. Despite this, the potential to identify individuals through running videos has not been thoroughly explored. The paper introduces a novel method that expands the feature-based approach for identifying individuals based on their running style. This work focuses on extracting the mutual information and location specific metric from the key gait poses of subjects in the testing and training datasets. Later on, the assignment of a testing sample to the training sample is accomplished using the proposed classification method. The experiments are conducted on KTH, OU-ISIR A, and Weizmann database. The efficiency of this method is demonstrated by the obtained experimental results. © 2024 IEEE.Item Performance Evaluation of Wireless Health and Remote Monitoring Network Throughput Under Varying Conditions Using NetSim(Institute of Electrical and Electronics Engineers Inc., 2024) Pabitha, B.; Vani, V.; Sanshi, S.The Wireless Body Area Network (WBAN), organized in/out of the human body region to form Wireless enabled Health and Remote monitoring Network (WHRN), is trending on the medical platform for efficient diagnosis by the physician without the patient's physical visit. This network is framed with different biological sensors in the regional area of the human body to sense unlike biological signals promptly. Wearable WHRN, like smart watches and mobile phones, can notify people about stress, heart rate, and other physiological nods. The technology developed enhances the treatment for the patient, but the security of the information transmitted over different mediums is vulnerable. WHRN is simulated using the NetSim standard tool. Network performance metrics and their plots are analyzed using various encryption standards to provide data transmission and diagnosis security. Security is the primary concern for physiological data sensed and transmitted over different mediums. © 2024 IEEE.Item Multi-factor Authentication and Data Integrity for WBAN Using Hash-Based Techniques(Springer Science and Business Media Deutschland GmbH, 2024) Pabitha, B.; Vani, V.; Sanshi, S.; Karthik, N.In recent days, a wireless body area network (WBAN) has been developed as part of the Internet of Things (IoT) with sensors and actuators in three different modes, building its network, i.e., in-body sensors, wearable sensors, and on-body sensors. The doctor’s access the data recorded and monitored by the sensor embedded in the patient to treat critical situations immediately. Maintaining data integrity and guarding against threats is necessary to secure sensitive patient information. Several people have proposed schemes for authenticating data access through formal and informal verification. In this research work, we carry out multi-factor authentication extensively using zero-knowledge proofs. The anomaly detection of the sensors is detected using machine learning algorithms, which help tune the sensors to their correct working conditions. The work aims to concentrate on sensor working conditions promptly and to handle attacks like masquerade, forgery, and key escrow attacks. To assess whether performance metrics are superior in computing cost, storage overhead, and communication overhead, utilize the BAN logic tool. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.Item Integrating artificial intelligence in aquaculture: opportunities, risks, and systemic challenges(Springer Science and Business Media Deutschland GmbH, 2025) M R, D.; Sanshi, S.; Singh, M.P.; Gupta, M.Aquaculture plays a significant role in the food chain and in rural economies. Continuous water quality monitoring, health management, real-time growth monitoring, and biomass estimation are critical aquaculture activities. Recent advances in computer vision, image processing, and Artificial Intelligence (AI), particularly in Machine Learning (ML) and Deep Learning (DL), enable the control, drive, and solve the problems related to daily real-time aquaculture activities. The performance of various ML and DL models and the quality and availability of public datasets in this domain remain underexplored, and the redefinition of the role of AI in aquaculture is the motivation for this study. This survey aims to analyse and evaluate various methods and datasets for monitoring water quality, estimating fish biomass, disease prediction, and behavioural analysis, to highlight recent developments and to seek the attention of researchers to address the challenges and concerns of aquaculture systems. Currently, there is no single, generalised AI model capable of performing all essential aquaculture activities using continuous time-series data generated from diverse, heterogeneous ponds across a wide geographical area. To address this gap, a 5G-enabled Federated Learning (FL) framework utilising Unmanned Aerial Vehicles (UAV) for cooperative data collection and model training is highly recommended. © The Author(s), under exclusive licence to Springer Nature Switzerland AG 2025.Item Enhanced mobility aware routing protocol for Low Power and Lossy Networks(Springer New York LLC barbara.b.bertram@gsk.com, 2019) Sanshi, S.; Jaidhar, C.D.Due to the technological advancement in Low Power and Lossy Networks (LLNs), sensor node mobility becomes a basic requirement for many extensive applications. Routing protocol designed for LLNs must ensure real-time data transmission with minimum power consumption. However, the existing mobility support protocols cannot work efficiently in LLNs as they are unable to adapt to the change in the network topology quickly. Therefore, we propose an Enhanced Routing Protocol for LLNs (ERPL), which updates the Preferred Parent (PP) of the Mobile Node (MN) quickly whenever the MN moves away from the already selected PP. Further, a new objective function that takes the mobility of the node into an account while selecting a PP is proposed. Performance of the ERPL has been evaluated with the varying system and traffic parameters under different topologies similar to most of the real-life networks. The simulation results showed that the proposed ERPL reduced the power consumption, packet overhead, latency and increased the packet delivery ratio as compared to other existing works. © 2017, Springer Science+Business Media, LLC, part of Springer Nature.