A Retrospective Study on “Effectiveness of Remote Patient Monitoring in Covid-19 patients"

Corona virus disease19 has spread over the world, affecting millions of people. It has put enormous strain on the global healthcare system. Due to frequent mutations, the pandemic is spreading rapidly. The world requires a technology that will facilitate the effective diagnosis, treatment, and discharge of COVID19 patients. A model like remote patient monitoring [RPM] makes it easier to handle Covid 19 patients. RPM helps in remotely diagnosis, treatment, as well as allowing for prompt interventions. The RPM makes use of mobile technology and IoT platforms to take clinical interventions. In this study out of 151 covid19 positive subjects 91% of them were shifted to home monitoring within 5 days of MVM monitoring with few readmissions. The study investigated the effectiveness of RPM in the Indian healthcare system, as well as the performance and usability of the Vigocare mobile application by patients and doctors.

Futuristic Research Perspectives of IoT Platforms

Future IoT innovation patterns will assist offices with getting the greatest proficiency and efficiency out of their hardware and assembling parts. IoT is an essential element of digital transformation enterprises in business and industrial sections. Service suppliers and utilities have also been taking on IoT to get pioneering services to keep competitive. Services with security, power management, asset presentation, healthcare effectiveness, and threat and agreement management must be resolved properly in order to enhance the IoT effectively and efficiently. As new tech turns up, hackers prepare to capture the benefits of its potential flaws, and this is precisely why enhancing the precautions of associated strategy is the top IoT technology development. Objectives of this chapter are to analyze and access the future of IoT in healthcare, security, education, and agriculture. This chapter will focus on edge computing, a hybrid approach to process the data that allows connected devices to distribute, compute, examine, and maintain data locally.

A Comprehensive Evaluation of Internet-of-Things Platforms

Internet of things (IoT) has attracted researchers in recent years as it has a great potential to solve many emerging problems. An IoT platform is missioned to operate as a horizontal key element for serving various vertical IoT domains such as structure monitoring, smart agriculture, healthcare, miner safety monitoring, smart home, and healthcare. In this chapter, the authors propose a comprehensive analysis of IoT platforms to evaluate their capabilities. The selected metrics (features) to investigate the IoT platforms are “ability to serve different domains,” “ability to handle different data formats,” “ability to process unlimited size of data from various context,” “ability to convert unstructured data to structured data,” and “ability to produce complex reports.” These metrics are chosen by considering the reporting capabilities of various IoT platforms, big data concepts, and domain-related issues. The authors provide a detailed comparison derived from the metric analysis to show the advantages and drawbacks of IoT platforms.

Methodological Approach to Assessing the Economic Efficiency of Digital Projects Applying Internet of Things Platforms

One of the key ones and most cost-effective technology from an economic point of view for the real sector is the Internet of Things (IoT) technology, which is usually provided in the form of Internet of Things (IoT) platforms, still does not have its own framework for assessing its economic efficiency. The author proposes a methodological approach based on a combination of classical methods of investment analysis and an architectural approach. From the information point of view the scientific work is based on cost-effectiveness studies of IoT projects, domestic and foreign scientific publications, IT cases and research on taxonomy of IoT platforms. The proposed approach may serve as the basis both for preparation of financial business cases and for facilitating the development of tools for objective assessment of the project initiatives attractiveness as part of implementation of the state digital development programs in Russia.

Designing Automated Deployment Strategies of Face Recognition Solutions in Heterogeneous IoT Platforms

In this paper, we tackle the problem of deploying face recognition (FR) solutions in heterogeneous Internet of Things (IoT) platforms. The main challenges are the optimal deployment of deep neural networks (DNNs) in the high variety of IoT devices (e.g., robots, tablets, smartphones, etc.), the secure management of biometric data while respecting the users’ privacy, and the design of appropriate user interaction with facial verification mechanisms for all kinds of users. We analyze different approaches to solving all these challenges and propose a knowledge-driven methodology for the automated deployment of DNN-based FR solutions in IoT devices, with the secure management of biometric data, and real-time feedback for improved interaction. We provide some practical examples and experimental results with state-of-the-art DNNs for FR in Intel’s and NVIDIA’s hardware platforms as IoT devices.

Patterns of business model innovation for advancing IoT platforms

PurposeThe emergence of Internet of Things (IoT) platforms in product companies opens up new data-driven business opportunities. This paper looks at the emergence of these IoT platforms from a business-model perspective.Design/methodology/approachThe study applies a mixed method with two research studies: Study I–a cluster analysis based on a quantitative survey, and Study II–case studies based on qualitative interviews.FindingsThe findings reveal that there is no gradual shift in a company's business model, but in fact three distinct and sequential patterns of business model innovations: (1) platform skimming, (2) platform revenue generation and (3) platform orchestration.Research limitations/implicationsThe results are subject to the typical limitations of both quantitative and qualitative studies.Practical implicationsThe results provide guidance to managers on how to modify the components of the business model (value proposition, value creation and/or delivery and profit equation) in order to enable platforms to advance.Social implicationsAs IoT platforms continue to advance, product companies achieve better performance in terms of productivity and profitability, and more easily secure competitive advantages and jobs.Originality/valueThe paper makes three original contributions: (1) it is the first quantitative study on IoT platforms in product companies, (2) identifies three patterns of business model innovations and (3) offers a first process perspective for understanding the sequence of these patterns as IoT platforms advance.

Key Criteria in the Choice of IoT Platforms in Spanish Companies

The level of implementation of IoT technology in Spanish companies is not low for a novel technology, but there are concerns that hinder its level of implementation from being higher: initial costs, security, and privacy. These concerns could be solved with the choice of the appropriate IoT platform, but it must be taken into account that there are numerous criteria that participate in this decision that influence each other. This could give rise to criteria not being considered at first, even though they should be taken into account in this choice. Existing studies do not consider this. Thus, the objective of this study was to find out what are the key criteria to be taken into account by Spanish companies when choosing an IoT platform. The criteria were located through a literary review, and classified according to their level of importance in this decision through a causal study carried out with the methodology of fuzzy cognitive maps. The results achieved showed that there were key criteria beyond the criteria directly implied by the concerns, such as stability, scalability, flexibility, and interoperability, and these new criteria acquired the same or greater importance.

Internet of Things-based Hydroponic: Literature Review

Hydroponics is a method of growing crops without using soil, with the benefits of controlling the environment and nutrients, conserving water, and reducing labor. The applied technology is used to improve results that have consistency. This research was conducted with the aim of knowing the IoT devices and platforms used in the development of IoT-based hydroponics. Data obtained from the website garuda.ristekbrin.go.id and www.sciencedirect.com from 2016 to 2021. This study is a literature review using the PRISMA method. This method is used for literature review using a systematic and structured basic framework. The results of this study indicate that the variables measured are Temperature, Potential Hydrogen (pH), Total Dissolve Solid, Water Temperature, Humidity, UV, Carbon Dioxide, Soil Moisture and Electrical Conductivity. The device used is the ESP8266, Arduino, and Raspberry PI with the MySQL, Thingspeak, Firebase, Domoticz, and Wyliodrin IoT Platforms.