Analytics of location-based big data for smart cities: Opportunities, challenges, and future directions

The growing ubiquity of location/activity sensing technologies and location-based services (LBS) has led to a large volume and variety of location-based big data (LocBigData), such as location tracking or sensing data, social media data, and crowdsourced geographic information. The increasing availability of such LocBigData has created unprecedented opportunities for research on urban systems and human environments in general. In this article, we first review the common types of LocBigData: mobile phone network data, GPS data, Location-based social media data, LBS usage/log data, smart card travel data, beacon log data (WiFi or Bluetooth), and camera imagery data. Secondly, we describe the opportunities fueled by LocBigData for the realization of smart cities, mainly via answering questions ranging from what happened and why did it happen to what's likely to happen in the future and what to do next. Thirdly, pitfalls of dealing with LocBigData are summarized, such as high volume/velocity/variety; non-random sampling; messy and not clean data; and correlations rather than causal relationships. Finally, we review the state-of-the-art research trends in this field, and conclude the article with a list of open research challenges and a research agenda for LocBigData research to help achieve the vision of smart and sustainable cities.

Automated summary

The article discusses the increasing prevalence of location/activity sensing technologies and location-based services, leading to a large volume and variety of location-based big data (LocBigData) and the opportunities and pitfalls it presents for research on urban systems and human environments. It also explores the role of LocBigData in realizing smart cities, summarizing research trends and challenges in the field.