Wearable sensors have received considerable interest over the past decade owing to their tremendous promise for monitoring the wearers’ health, fitness, and their surroundings. However, only limited attention has been directed at developing wearable chemical sensors that offer more comprehensive information about a wearer’s well-being. The development of wearable chemical sensors faces multiple challenges on various fronts. This perspective reviews key challenges and technological gaps impeding the successful realization of effective wearable chemical sensor systems, related to materials, power, analytical procedure, communication, data acquisition, processing, and security. Size, rigidity, and operational requirements of present chemical sensors are incompatible with wearable technology. Sensor stability and on-body sensor surface regeneration constitute key analytical challenges. Similarly, present wearable power sources are incapable of meeting the requirements for wearable electronics owing to their l...

Wearable Chemical Sensors: Present Challenges and Future Prospects

This article investigates challenges pertaining to business model design in the emerging context of the Internet of Things (IOT). The evolution of business perspectives to the IOT is driven by two underlying trends: i) the change of focus from viewing the IOT primarily as a technology platform to viewing it as a business ecosystem; and ii) the shift from focusing on the business model of a firm to designing ecosystem business models. An ecosystem business model is a business model composed of value pillars anchored in ecosystems and focuses on both the firm's method of creating and capturing value as well as any part of the ecosystem's method of creating and capturing value. The article highlights three major challenges of designing ecosystem business models for the IOT, including the diversity of objects, the immaturity of innovation, and the unstructured ecosystems. Diversity refers to the difficulty of designing business models for the IOT due to a multitude of different types of connected objects combined with only modest standardization of interfaces. Immaturity suggests that quintessential IOT technologies and innovations are not yet products and services but a "mess that runs deep". The unstructured ecosystems mean that it is too early to tell who the participants will be and which roles they will have in the evolving ecosystems. The study argues that managers can overcome these challenges by using a business model design tool that takes into account the ecosystemic nature of the IOT. The study concludes by proposing the grounds for a new design tool for ecosystem business models and suggesting that "value design" might be a more appropriate term when talking about business models in ecosystems. New web-based business models being hatched for the Internet of Things are bringing together market players who previously had no business dealings with each other. Through partnerships and acquisitions, […] they have to sort out how they will coordinate their business development efforts with customers and interfaces with other stakeholders.

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Designing Business Models for the Internet of Things

Patient Monitoring System Based on Internet of Things

Industrial Internet of Things and its Applications in Industry 4.0: State of The Art

Internet of Things (IoT) is widely accepted technology in both industrial as well as academic field. The objective of IoT is to combine the physical environment with the cyber world and create one big intelligent network. This technology has been applied to various application domains such as developing smart home, smart cities, healthcare applications, wireless sensor networks, cloud environment, enterprise network, web applications, and smart grid technologies. These wide emerging applications in variety of domains raise many security issues such as protecting devices and network, attacks in IoT networks, and managing resource-constrained IoT networks. To address the scalability and resource-constrained security issues, many security solutions have been proposed for IoT such as web application firewalls and intrusion detection systems. In this paper, a comprehensive survey on Intrusion Detection System (IDS) for IoT is presented for years 2015–2019. We have discussed various IDS placement strategies and IDS analysis strategies in IoT architecture. The paper discusses various intrusions in IoT, along with Machine Learning (ML) and Deep Learning (DL) techniques for detecting attacks in IoT networks. The paper also discusses security issues and challenges in IoT.

Oscar Hoyos

Papers

Interaction System based on Internet of Things as Support for Education