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Selecting and using the same health monitoring devices for a particular problem is a tedious task. This paper aims to provide a comprehensive review of 40 research papers giving the Smart health monitoring system using Internet of things (IoT) and Deep learning.

Health Monitoring Systems play a significant role in the healthcare sector. The development and testing of health monitoring devices using IoT and deep learning dominate the healthcare sector.

In addition, the detailed conversation and investigation are finished by techniques and development framework. Authors have identified the research gap and presented future research directions in IoT, edge computing and deep learning.

The gathered research articles are examined, and the gaps and issues that the current research papers confront are discussed. In addition, based on various research gaps, this assessment proposes the primary future scope for deep learning and IoT health monitoring model.

In an era overshadowed by the alarming consequences of climate change and the escalating peril of recurring floods for communities worldwide, the significance of proficient disaster risk management has reached unprecedented levels. The successful implementation of disaster risk management necessitates the ability to make informed decisions. To this end, the utilization of three-dimensional (3D) visualization and Web-based rendering offers decision-makers the opportunity to engage with interactive data representations. This study aims to focus on Thiruvananthapuram, India, where the analysis of flooding caused by the Karamana River aims to furnish valuable insights for facilitating well-informed decision-making in the realm of disaster management.

This work introduces a systematic procedure for evaluating the influence of flooding on 3D building models through the utilization of Web-based visualization and rendering techniques. To ensure precision, aerial light detection and ranging (LiDAR) data is used to generate accurate 3D building models in CityGML format, adhering to the standards set by the Open Geospatial Consortium. By using one-meter digital elevation models derived from LiDAR data, flood simulations are conducted to analyze flow patterns at different discharge levels. The integration of 3D building maps with geographic information system (GIS)-based vector maps and a flood risk map enables the assessment of the extent of inundation. To facilitate visualization and querying tasks, a Web-based graphical user interface (GUI) is developed.

The efficiency of comprehensive 3D building maps in evaluating flood consequences in Thiruvananthapuram has been established by the research. By merging with GIS-based vector maps and a flood risk map, it becomes possible to scrutinize the extent of inundation and the affected structures. Furthermore, the Web-based GUI facilitates interactive data exploration, visualization and querying, thereby assisting in decision-making.

The study introduces an innovative approach that merges LiDAR data, 3D building mapping, flood simulation and Web-based visualization, which can be advantageous for decision-makers in disaster risk management and may have practical use in various regions and urban areas.

The study explores and builds theories in Customer Perceived Values (CPVs) that drive counterfeit buying intention, using a Grounded Theory Approach (GTA) in an emerging market, India.

Counterfeit studies have either resorted to a survey approach or modelling approach in investigating various aspects and dimensions. This study, among a few, attempted a GTA in building theory on CPVs. Based on the observations and recorded responses that emerged through several Focus Group Discussions (FGDs); conducted in two metropolitan cities (India), newer insights into this illicit phenomenon of “Counterfeiting” were derived.

Adding to the counterfeit literature, the study presents a comprehensive view of the CPVs. Findings reveal economic, socio-normative, pleasure-based, euphemistic, acquisition-centrality, self-regulating, situational and sustainable consumption values that influence counterfeit attitudes and in turn impact counterfeit buying intentions. Although Economic Values (ECV) have been the primary motivation for counterfeit purchase, complex and newer values that emerged through this research study bears significance.

As a single point of reference, this study will provide impetus to scholars and academicians in expanding the counterfeit research domain. While aiding policymakers and marketers in further understanding this illicit practice, it will also guide brand managers in strategizing their offerings and reaching out to the masses with strong brand aesthetic values.

Based on a systematic literature review using the 4 Ws framework, this study is one of the few attempts that has adopted a GTA to explore and develop theories on CPVs in counterfeit research.