Smart E-Healthcare with Internet of Things: Current Trends, Challenges, Solutions, and Technologies

Author(s):  
Lavanya Sharma ◽  
Pradeep K. Garg ◽  
Sunil K. Khatri
Author(s):  
Aldo D. Fabregas ◽  
Paul Crawford ◽  
Rodrigo Mesa ◽  
Agustina Calatayud

The intended purpose of an intelligent transportation systems (ITS) project is to automate operations through device-to-device connectivity. These devices generally represent stakeholder’s endpoints and expose interfaces to automated operations. Current trends in communication allow more applications and devices to perform functions traditionally allocated to the transportation ITS infrastructure. This connected environment of industrial internet of things presents design challenges because of the diversity of stakeholders, interfaces, and the messages among them. This may require new ways in which ITS planning can handle the scale and complexity of these highly connected systems. This work focuses on the modeling of the architecture of a freight-focused ITS application, including maritime ports. The proposed model integrates stakeholders, behaviors, and messages using the Systems Modeling Language (SysML). The key contribution of this work is to demonstrate the creation of an executable SysML model for an ITS application without sacrificing the typical Systems Engineering Management Plan artifacts (e.g., requirements traceability matrices and interface control documents). At the same time, the proposed model provides a re-usable pattern to support parametric analysis of candidate architectures with respect to any measure of effectiveness. This allows establishing a single source of architecture definition and having multiple architecture specializations depending on the measure of effectiveness being evaluated. Recommendations for implementation and integration with existing ITS tools are provided.


Author(s):  
S. Kavitha ◽  
J. V. Anchitaalagammai ◽  
S. Nirmala ◽  
S. Murali

The chapter summarizes the concepts and challenges of DevOps in IoT, DevSecOps in IoT, integrating security into IoT, machine learning and AI in IoT of software engineering practices. DevOps is a software engineering culture and practice that aims at unifying software development (Dev) and software operation (Ops). The main characteristic of DevOps is the automation and monitoring at all steps of software construction, from integration, testing, releasing to deployment and infrastructure management. DevSecOps is a practice of integrating security into every aspect of an application lifecycle from design to development.


Author(s):  
Shivom Aggarwal ◽  
Abhishek Nayak

Mobile technologies have given rise to tremendous amounts of data in real-time, which can be unstructured and uncertain. This growth can be attributed as Mobile Big Data and provides new challenges and opportunities for innovation. This chapter attempts to define the concept of Mobile Big Data, provide description of various sources of Mobile Big Data and discuss SWAI (Sources Warehousing Analytics Insights) model of Big Data processing. To understand this complex concept, it is important to visualize the Big Data ecosystem, respective players. Moreover, mobile computing, Internet of things, and other associated technologies have been discussed in light of marketing and communications based applications. The current trends in Mobile Big Data and associated value chain help us understand where the next frontiers of innovation are and how one can create value. This is linked to the future aspects of the Mobile Big Data and evolution of technologies from now onwards.


Author(s):  
S. Kavitha ◽  
J. V. Anchitaalagammai ◽  
S. Nirmala ◽  
S. Murali

The chapter summarizes the concepts and challenges of DevOps in IoT, DevSecOps in IoT, integrating security into IoT, machine learning and AI in IoT of software engineering practices. DevOps is a software engineering culture and practice that aims at unifying software development (Dev) and software operation (Ops). The main characteristic of DevOps is the automation and monitoring at all steps of software construction, from integration, testing, releasing to deployment and infrastructure management. DevSecOps is a practice of integrating security into every aspect of an application lifecycle from design to development.


Author(s):  
Sathiya Narayanan ◽  
Nikshith Narayan Ramesh ◽  
Amit Kumar Tyagi ◽  
L. Jani Anbarasi ◽  
Benson Edwin Raj

In the recent years, innovations such as Augmented Reality (AR), Virtual Reality (VR), and internet of things have enhanced user experience dramatically. In general, AR is completely different from VR and provides real-time solutions to users by projecting layers of information on real-world environments. Advancements in computer-generated sensory have made the concept of believable virtual environments a reality. With the availability of such technologies, one can investigate “how these technologies can be applied beyond gaming or other useful applications” and “how further improvements can be made to allow for full digital immersion.” This chapter provides a detailed description about AR and VR, followed by interesting real-world examples of AR applications. In addition, this chapter discusses the issues and challenges faced with AR/VR with a motivation of exploring the options for improvement.


2016 ◽  
pp. 1796-1816
Author(s):  
Shivom Aggarwal ◽  
Abhishek Nayak

Mobile technologies have given rise to tremendous amounts of data in real-time, which can be unstructured and uncertain. This growth can be attributed as Mobile Big Data and provides new challenges and opportunities for innovation. This chapter attempts to define the concept of Mobile Big Data, provide description of various sources of Mobile Big Data and discuss SWAI (Sources Warehousing Analytics Insights) model of Big Data processing. To understand this complex concept, it is important to visualize the Big Data ecosystem, respective players. Moreover, mobile computing, Internet of things, and other associated technologies have been discussed in light of marketing and communications based applications. The current trends in Mobile Big Data and associated value chain help us understand where the next frontiers of innovation are and how one can create value. This is linked to the future aspects of the Mobile Big Data and evolution of technologies from now onwards.


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