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In the recent past, mobile technologies that track the movement of people, freight and vehicles have evolved rapidly. The major categories of such technologies are reviewed and a number of attributes for classification are proposed. The willingness of people to engage in such technologically based surveys and the reported biases in the make-up of the sample obtained are reviewed. Lessons are drawn about the nature of the samples that can be achieved and the representativeness of such samples is discussed. Data processing is addressed, particularly in terms of the processing requirements for logged data, where additional travel characteristics required for travel analysis may need to be imputed. Another issue explored is the reliability of data entered by respondents in interactive devices and concerns that may arise in processing data collected in real time for prompting or interrogating respondents. Differences, in relation to the data user, between data from mobile devices and data from conventional self-report surveys are discussed. Potentials that may exist for changes in modelling from using such data are explored. Conclusions are drawn about the usefulness and limitations of mobile technologies to collect and process data. The extent to which such mobile technologies may be used in future, either to supplement or replace conventional methods of data collection, is discussed along with the readiness of the technology for today and the advances that may be expected in the short and medium term from this form of technology.

In the telecommunication industry we observe trends such as unbundling, convergence, and new business models. To accelerate innovation, mobile telecommunication companies are more and more working together with companies from other industrial sectors (such as media and IT). The Cyclic Innovation Model helps to understand all those activities in this rather chaotic business environment. This particularly applies to mobile telecommunication companies that are developing mobile data innovations (such as Lucio). All those innovations are steps along a transition path towards a wireless future.

The impact of mitigating flood occurrence in the rural and urban areas has become crucial as it has affected government policies for countries that are prone to flood disaster. Efforts and funds have been put up to a higher level of capabilities to ensure that coping and managing flood disaster could be resolved. Several initiatives made in managing flood are: effectively monitoring the potential at-risk inundated area, improving the river water irrigation and drainage and undertaking the environmental pollution. This chapter basically focusses more on the improvement of flood monitoring system device at the potential flood area. The approach of ubiquitous mobile SCADA offers a low-cost, portable, and small in size flood monitoring system device with easily accessible data. An easy web monitoring of environment surrounding anywhere and at any time offers a real-time data updated with a very minimum delay of each and every environment data required. There are several sensors like ultrasonic, sound, temperature and humidity, water drop and vibration sensors are equipped together with one small monitoring system platform. The alert of water level condition is notified through a beeping buzzer and light LED notation of various colors of green, yellow and red, which notify any increase of water exceeded. The platform is powered by a rechargeable battery that allows the platform to be mobile and portable. Hence, flood monitoring system platform promotes a low-cost, easy-to-handle and ubiquitous data updated device for a better monitoring system platform.

Purpose — In this chapter, we will review several alternative methods of collecting data from mobile phones for human mobility analysis. We propose considering cellular network location data as a useful complementary source for human mobility research and provide case studies to illustrate the advantages and disadvantages of each method.

Methodology/approach — We briefly describe cellular phone network architecture and the location data it can provide, and discuss two types of data collection: active and passive localization. Active localization is something like a personal travel diary. It provides a tool for recording positioning data on a survey sample over a long period of time. Passive localization, on the other hand, is based on phone network data that are automatically recorded for technical or billing purposes. It offers the advantage of access to very large user populations for mobility flow analysis of a broad area.

Findings — We review several alternative methods of collecting data from mobile phone for human mobility analysis to show that cellular network data, although limited in terms of location precision and recording frequency, offer two major advantages for studying human mobility. First, very large user samples – covering broad geographical areas – can be followed over a long period of time. Second, this type of data allows researchers to choose a specific data collection methodology (active or passive), depending on the objectives of their study. The big mobile phone localization datasets have provided a new impulse for the interdisciplinary research in human mobility.

Originality/value of chapter — We propose considering cellular network location data as a useful complementary source for transportation research and provide case studies to illustrate the advantages and disadvantages of each proposed method. Mobile phones have become a kind of “personal sensor” offering an ever-increasing amount of location data on mobile phone users over long time periods. These data can thus provide a framework for a comprehensive and longitudinal study of temporal dynamics, and can be used to capture ephemeral events and fluctuations in day-to-day mobility behavior offering powerful tools to transportation research, urban planning, or even real-time city monitoring.

New mobile platforms, connected seamlessly to the Internet via wireless access, become increasingly more powerful as each day passes. Smartphones and tablet computers, as well as other ultraportable devices, have already gained enough critical mass to be considered mainstream devices, being present in the daily lives of millions of higher education students. Whole firms, devoted solely to developing high-quality and high engagement content to these devices, have emerged, populating an application market of thousands of teaching applications (apps) focused on diverse higher education topics, from physics and calculus to anatomy and law. Many universities throughout the world have already adopted or are planning to adopt mobile technologies in many of their courses as a better way to connect students with the subjects they are studying. These new mobile platforms allow students to access content anywhere/anytime to immerse himself/herself into that content (alone or interacting with teachers or colleagues via web communication forms) and to interact with that content in ways that were not previously possible (via touch and voice recognition technologies, for instance). The study of such technologies and their possible uses for higher education, as well as the impacts they can have on stimulating more active participation and engagement with the course subjects and research in higher education, while at the same time fostering collaboration among students and even different institutions, is the goal of the proposed chapter. Through the evaluation of the teacher/student acceptance and adoption of such mobile technologies, this chapter plans to provide a thorough overview of the possibilities and consequences of mobile learning in higher education environments as a gateway to ubiquitous learning – perhaps the ultimate form of learner engagement, since it allows the student to learn, access and interact with important content in any way or at any time or place she/he might want.

Introduction: Digitalization has become crucial in our daily lives. The rapid rise of new technologies and high interest levels of individuals enforces companies to invest in these technologies. Nowadays, as customers are willing to try new experiences, companies dynamically start to find new ways to develop their products and services. One of the most popular technologies used by companies to improve their services is the Internet of Things (IoT) technologies. Education, health, transportation, retail, and energy are some of the industries in which the IoT is frequently being used. As security concerns of individuals arose and willingness to remote control increases, innovative and technological projects with IoT applications are engaged in the construction and real estate sector.

Aim: The purpose of this chapter is to explore IoT applications within the new generation smart home systems. In this framework, the effect of IoT technologies on architectural structure of the smart home and operating systems as well as IoT and mobile-supported customer-focused applications and difficulties are analyzed.

Method: The study is designed as an exploratory study. The data are obtained from face-to-face interviews with companies operating on technology-based commercial and residential projects. Descriptive analysis method is used to analyze data. Sample selection was carried out by the judicial sampling technique.

Findings: The results showed that smart home systems offer several customer-oriented experiences to their users like personalized accessibility, comfort, time control, and energy savings. Wired and wireless communication protocols are included in the architecture of the system. Linux core software-based Android and iOS operating systems are used in order to enhance personal accessibility. However, some difficulties are noticed in the sector. Lack of information and internet infrastructure of companies that install electrical set-up are mentioned. Contractors, after sales service support, and customer-oriented applications are evaluated.