Evaluation of Big Data within the Context of the Protection of Personal Data and Competition Law

In order to sustain their presence in the market, personal data acquirers must obtain, store, and process personal data from sources that feed data such as social media shares, shopping records, and sensor networks. On the other hand, the problem of conformity of real and legal persons whose personal data are processed within the framework of personal data law brings about many legal problems and requires a profound research rather than a limited examination. The fact that a small number of enterprises create dominant power by using big data in market strategy has led to data-dependent companies or markets. Due to the effects that big data caused in the market, there is a need to address many problems in the field of competition law as well as the dimension of privacy and personal rights. In this context, the conflict of interest between the economic interest created by big data and the legal principles of personal data will be addressed and compared with regard to Turkish law and foreign law practices by discussing the relationship between big data and competition law.

Big Data and Enterprise Applications

Today, a company continues its activities in a highly competitive environment regardless of the sector in which it operates. An important point has been emphasized in many developments by experienced managers and academics which have been released to the public. From marketing to finance, human resource management, auditing and planning, all business processes have entered an incredible innovative process. One of the topics in this process is big data. When cumulative data are not used, they cannot transcend being huge piles of garbage. However, it is not possible to analyze such large, complex, and dynamic data via conventional methods. At this point, the concept of big data has emerged. In this study, after the explanation and definition of the concept, a vast literature review was conducted in order to present the relationship of big data with IoT, big data-related topics, and academic researches on big data. Afterwards, real-life enterprise applications were exemplified from various industries.

Digital Transformation of Supply Chains With Mobile IoT

Today, mobile IoT (m-IoT) connectivity is one of the significant enablers of Supply Chain 4.0 with its capabilities of secure connectivity over large areas at low cost and with low device complexity. The purpose of this chapter is to shed light on the evolution of m-IoT paradigm within context of supply chain management. The potential of LTE, 4G, and future 5G technologies and the impact of m-IoT enabling technologies, LTE-M, and NB-IoT on digital transformation of SCM are investigated through commercial deployments; current status and future directions are discussed in terms of supply chain efficiency and supply chain visibility. Accordingly, this chapter first outlines the technical architecture and features of NB-IoT and LTE-M technologies and then explores how m-IoT connectivity is creating value for supply chains through commercial deployment examples. Exploration of m-IoT potential on supply chain operations will ensure new insights and opportunities for further advancement and evolution of IoT paradigm as a means of productivity.

How Can Industrial Internet of Things (IIoT) Improve Enterprise Productivity?

This chapter gives brief information about internet of things (IoT) and then detailed knowledge of industrial internet of things (IIoT). Internet of things applications can be seen in different areas, such as smart cars, smart homes, smart cities, agriculture, healthcare, industry, etc. This study focuses on the industrial part. Industrial internet of things (IIoT) means internet of things (IoT) applications for industrial usage. IIoT give a chance to enterprise for tracking supply chains, monitoring production line operations, and real-time consumption of energy, managing stock, and transportation decisions. This study used case study method for developing theory about IIoT's contribution to enterprise productivity. IIoT applications can be adapted to which operations of the enterprise, and how it will contribute to enterprise productivity is explained in this chapter. The chapter discusses the projects that are within the vision of IIoT but not yet implemented and concludes with suggestions for future studies.

Industry 4.0 and the Internet of Things (IoT)

In this study, the periodical differences of industrial revolutions, which is one of the effects of technological developments in the industrial field, and the last stage of it are mentioned. With the latest industrial revolution called Industry 4.0, machines work in harmony with technology at every stage of industrial areas. This period, known as Industry 4.0 or the fourth industrial revolution, refers to the system in which the latest production technologies, automation systems, and the technologies that make up this system exchange data with each other. In addition to the information technologies and automation systems used in Industry 3.0, industrial production has gained a whole new dimension with the use of the internet. With internet networks, machines, operators, and robots now work in harmony. At this point, the concept of internet of objects becomes important. Therefore, another focus of the study is the concept of internet of objects. There are some assumptions about the uses, benefits, and future status of the internet of things.

Internet of Things in Disaster Logistics Productivity

It is possible to carry out logistics operations in a highly efficient and reliable manner with internet of things technologies. These technologies increase the added value of logistics activities and expand their benefits in the supply chain. Logistic activities are a sine qua non of disaster management. The active use of internet of things during disaster preparedness stage, during disaster, and after disaster, in warehouse and material management, fleet and transport management is an important technological milestone which will greatly increase productivity. Right place, right time, right quantity, right quality, and right price rule is known as 5 Right rule in logistics. In disaster logistics, only the price is excluded from these rules because it does not matter if human life is concerned. Strategic approaches, which are provided by IoT technology, are key to efficiently carry out 5 Right rule in disaster logistics.

Productivity in Digital Transformation

The chapter presents the differences between the concepts of digitalization and digital transformation. The pioneers of digital transformation in the historical process and their use in different sectors are explained with examples. The relationship between digital transformation and productivity is discussed, and the enablers that allow this relationship are explained in detail. Turkey's digital transformation process shared by explaining the vision of public and private sectors. It is also explained that SMEs can do in digital transformation process in order to gain competitive advantage.

An Architectural Layer Classification of Energy Conservation Techniques in Internet of Things

Using three-layered architecture IoT can be methodically understood. These layers are sensing and data collection layer, data processing and network layer, and application layer. In sensing and data collection layer, sensors are used to sense its surrounding environment. The processing layer is moreover like a middleware layer. The application layer is liable for conveying a particular facility to the client. All of these layers are energy constrained. Hence, it is a sensitive issue to efficiently reduce the energy consumption in IoT. To increase energy efficiency in IoT networks, a large number of techniques have been developed by different researchers. The chapter introduces a classification of energy conservation techniques based on the IoT architecture layer in which they work. The energy-efficiency techniques are also discussed in brief. The chapter also analyses the techniques with respect to their advantages and disadvantages. Moreover, future directions have also been presented in brief.

Technology Project Portfolio Selection in Industry 4.0

Industry 4.0 transformation is creating changing dynamics in business and becoming a highly important concept that requires the support of top management for projects and investment. As a result of transformation processes, Industry 4.0 develops more productive and continuous systems, and companies have been searching for the right adaptation of this transformation. In order to succeed in this Industry 4.0 transition, decision-making regarding the selection of profitable technology projects is a key point for companies. The proposed model incorporates two important goals: profit maximization by selecting technology projects and the development of simulation-based optimization with a three-step stage-gate model for technology project portfolio management under conditions such as resources, costs, and the probabilities of completion of stages and success. The stage-gate system contributes to the model development through the various steps from idea to launch and helps manage the Industry 4.0 transition process to improve effectiveness and efficiency.

Internet of Things (IoT) in Healthcare Systems

Health is the basic ability that people need to perceive, feel, and act effectively in their lives. Therefore, it constitutes the primary element in the development of the individual and in the environment in which people belong. In order to strengthen health services in the days we live, comprehensive researches are being conducted under the title of Health 4.0 to investigate various technologies. The internet of things (RFID, cloud computing, etc.) is developed to connect existing medical resources and provide patients with the most reliable, smartest, and most effective healthcare services. The aim of this chapter is to summarize the most basic applications of IoT in the health industry.