Internet of Things and Big Data Analytics for Smart and Connected Communities

This paper promotes the concept of smart and connected communities SCC, which is evolving from the concept of smart cities. SCC are envisioned to address synergistically the needs of remembering the past (preservation and revitalization), the needs of living in the present (livability), and the needs of planning for the future (attainability). Therefore, the vision of SCC is to improve livability, preservation, revitalization, and attainability of a community. The goal of building SCC for a community is to live in the present, plan for the future, and remember the past. We argue that Internet of Things (IoT) has the potential to provide a ubiquitous network of connected devices and smart sensors for SCC, and big data analytics has the potential to enable the move from IoT to real-time control desired for SCC. We highlight mobile crowdsensing and cyber-physical cloud computing as two most important IoT technologies in promoting SCC. As a case study, we present TreSight, which integrates IoT and big data analytics for smart tourism and sustainable cultural heritage in the city of Trento, Italy

Tourism and the smartphone app: capabilities, emerging practice and scope in the travel domain.

Based on its advanced computing capabilities and ubiquity, the smartphone has rapidly been adopted as a tourism travel tool.With a growing number of users and a wide varietyof applications emerging, the smartphone is fundamentally altering our current use and understanding of the transport network and tourism travel. Based on a review of smartphone apps, this article evaluates the current functionalities used in the domestic tourism travel domain and highlights where the next major developments lie. Then, at a more conceptual level, the article analyses how the smartphone mediates tourism travel and the role it might play in more collaborative and dynamic travel decisions to facilitate sustainable travel. Some emerging research challenges are discussed

Big Data for Traffic Estimation and Prediction: A Survey of Data and Tools

Big data has been used widely in many areas including the transportation industry. Using various data sources, traffic states can be well estimated and further predicted for improving the overall operation efficiency. Combined with this trend, this study presents an up-to-date survey of open data and big data tools used for traffic estimation and prediction. Different data types are categorized and the off-the-shelf tools are introduced. To further promote the use of big data for traffic estimation and prediction tasks, challenges and future directions are given for future studies