Public Administration Curriculum-Based Big Data Policy-Analytic Epistemology

The equilibration that underscores the internet of things (IoT) and big data analytics (BDA) cannot be underestimated at the behest of real-life social challenges and significant policy data generated to redress the concerns of epistemic communities, such as political policy actors, stakeholders, and the citizenry. The cognitive balancing of new information gathered by BDA and assimilated across the IoT is at the crossroads of ascertaining how the growing increases of such BDA can be better managed to transition from the big data state of disequilibration to reach a more stable equilibrium of policy data usefulness. In the quest for explicating the equilibration of policy data usefulness, an account of the curriculum-based MPA policy analysis and analytics concentration program at Norwich University is described as a case example of big data policy-analytic epistemology. The case study offers a symbolic ideology of an IoT action-learning solution model as a recommendation for fostering the stable equilibration of policy data usefulness.

Personal Data Privacy and Protection in the Meeting, Incentive, Convention, and Exhibition (MICE) Industry

With the new developments in information technologies, personal and business data have become easily accessible through different channels. The huge amounts of personal data across global networks and databases have provided crucial benefits in a scientific manner and many business opportunities, also in the meeting, incentive, convention, and exhibition (MICE) industry. In this chapter, the authors focus on the analysis of MICE industry with regards to the new regulation (GDPR) of personal data protection of all EU citizens and how the industry professionals can adapt their way of business in light of this new regulation. The authors conducted an online interview with five different meetings industry professionals to have more insight about the data produced with its content and new regulations applied to the industry. The importance of personal data privacy and protection is discussed, and the most suitable anonymization techniques for personal data privacy are proposed.

Artificial Neural Network Models for Large-Scale Data

Artificial intelligence (ARTINT) and information have been famous fields for many years. A reason has been that many different areas have been promoted quickly based on the ARTINT and information, and they have created many significant values for many years. These crucial values have certainly been used more and more for many economies of the countries in the world, other sciences, companies, organizations, etc. Many massive corporations, big organizations, etc. have been established rapidly because these economies have been developed in the strongest way. Unsurprisingly, lots of information and large-scale data sets have been created clearly from these corporations, organizations, etc. This has been the major challenges for many commercial applications, studies, etc. to process and store them successfully. To handle this problem, many algorithms have been proposed for processing these big data sets.

Big Data Analytics and Internet of Things in Industrial Internet in Former Soviet Union Countries

The purpose of this chapter is to explore the integration of three new concepts—big data, internet of things, and internet signs—in the countries of the former Soviet Union. Further, the concept of big data is analyzed. The internet of things is analyzed. Information on semiotics is given, and it reduces to the notion of internet signs. Context concepts and the contribution of big data, internet of things, and internet of signs to contextual simplification are analyzed. The chapter briefly outlines some potential applications of the integration of these three concepts. The chapter briefly discusses the contribution of the study and gives some extensions. These applications included continuous monitoring of accounting data, continuous verification and validation, and use of big data, location information, and other data, for example, to control fraudsters in the countries of the former Soviet Union.

Applications of Big Data and Green IoT-Enabling Technologies for Smart Cities

In recent years, enormous amounts of digital data have been generated. In parallel, data collection, storage, and analysis technologies have developed. Recently, there has been an increasing trend of people moving towards urban areas. By 2030 more than 60% of the world's population will live in an urban environment. Urban areas are big data resource because they include millions of citizens, technological devices, and vehicles which generate data continuously. Besides, rapid urbanization brings many challenges, such as environmental pollution, traffic congestion, health problems, energy management, etc. Some policies for countries are required to cope with urbanization problems. One of these policies is to build smart cities. Smart cities integrate information and communication technology and various physical devices connected to the network (the internet of things or IoT) to both improve the quality of government services and citizen welfare. This chapter presents a literature review of big data, smart cities, IoT, green-IoT concepts, using technology and methods, and applications worldwide.

Big Data and IoT Opportunities for Small and Medium-Sized Enterprises (SMEs)

The advancement of technology and emergence of internet of things (IoT) has exponentially caused a data explosion in the 21st century era. As such, the arrival of IoT is set to revolutionize the development of the small and medium-sized enterprise (SME) organizations by shaping it into a more universal and integrated ecosystem. Despite evidential studies of the potential of advanced technologies for businesses, the SMEs are apprehensive towards new technologies adoption such as big data analytics and IoT. Therefore, the aim of this chapter is to provide a holistic study of big data and IoT opportunities, challenges, and applications within the SMEs context. The authors hope that the outcome of this study would provide foundational information on how the SMEs can partake with the new wave technological advancement and in turn, spurring more SMEs for adoption.

Green Internet of Things (G-IoT)

Smart world is envisioned via the fusion of diverse technologies like sensor communications, cloud computing, internet of things, AI, machine and deep learning. No doubt, new technologies bring revolution and innovation in every aspect of human life, but they are accompanied by lots of limitations in terms of energy wastage, environmental hazards like carbon or other chemical emissions, extreme consumption of natural or renewable sources and greenhouse effects. In order to minimize the negative impact of these technologies on the environment, it is utmost important to move towards green technology. That is the reason researchers are working hard and moving towards green computing, ICT, and IoT. This chapter explores an in-depth analysis of principles of G-IoT, making significant progress towards improvising the quality of life and sustainable environment. In addition to this, the chapter outlines various Green ICT technologies explores potential towards diverse real-time areas and also highlights various challenges acting as a barrier towards G-IoT implementation in the real world.

Creating a Research Laboratory on Big Data and Internet of Things for the Study and Development of Digital Transformation

This chapter discusses the problems associated with the design of the business model in the new context of big data and the internet of things to create a research laboratory for studying and improving digital transformations. The development of business prospects for IOT is due to two main trends: 1) the change of focus from IOT viewing primarily as a technology platform for viewing it as a business ecosystem and 2) the transition from focusing on the business model in general to the development of business models of ecosystems. In the chapter, the business model of the ecosystem is considered as a model consisting of signs fixed in ecosystems and focuses on creating the cost of the laboratory and fixing the value of the ecosystem in which the created laboratory operates.

Role of Communication Technologies for Smart Applications in IoT

New technologies like ICTs (information and communications technologies) are recognized as key players in building smart applications for IoT. The use of sensors and actuators can efficiently control the whole communication system and will provide application-based solutions for smart applications. ICT provides industry-leading cellular machine-to-machine (M2M) technologies including industrial-grade embedded modules with cloud platforms, long life spans, expert application development assistance, and more. ICT M2M connectivity helps utilities to lower down the operating costs by eliminating the need to deploy and maintain communications infrastructure separately.

Critical Issues in the Invasion of the Internet of Things (IoT)

In this chapter, the authors collected data from issues related to threats in the applications of IoT-based technologies that describe the security and privacy issues from 30 peer reviewed publications from 2014 to 2017. Further, they analyzed each threat type and its percentages in each application of the internet of things. The results indicated that the applications of smart transportation (20%) face the highest amount of security and privacy issues followed by smart home (19%) and smart cities (18%) compared to the rest of the applications. Further, they determined that the biggest threats were denial of service attack (9%) followed by eavesdropping (5%), man in the middle (4%), and replay (4%). Denial of service attacks and man in the middle attack are active attacks that can severely damage human life whereas eavesdropping is a passive attack that steals information. This study has found that privacy issues have the biggest impacts on people. Therefore, researchers need to find possible solutions to these threats to improve the quality of IoT applications.