1.This thematic issue
Intelligent environments strongly depend on the data provided by different types of sensors. Thus, the continuous innovation in the development of new sensors is a hot research line in our scientific community. Whilst the main corpus of this research in smart environments is devoted to build new physical or hard sensors, such as those employed in smart homes or smart cities, we should also add the soft sensors to the picture, i.e. sensors that gather data from social networks, as they may complement the data provided by the physical ones or even provide data which hard sensors cannot measure (e.g., citizens’ opinions). Some of the most relevant trends in the use of soft sensors in smart environments are found in the use of data collected from Online Social Networks for the identification of the land use in cities  or detection of fake user’s location , among others.
This Thematic Issue presents some of the latest advances in the integration of both types of sensors in smart environments with the aim of providing novel ideas and methods of obtaining and using data. We wish to thank our colleagues Dr. Francisco Falcone (University of Navarra), Dr. Mounir Ghogho (International University of Rabat) and Dr. Essaid Sabir (Hassan II University of Casablanca) for managing this thematic issue as guest editors.
The following is the list of upcoming issues of JAISE:
– July 2020: Regular Issue.
– September 2020: Thematic Issue on Smart Environments and Ambient Intelligence in Agricultural Technology
– November 2020: Regular Issue.
– January 2021: Thematic Issue on Location-aware Computing to Mobile Services Recommendation: Theory and Practice.
– March 2021: Regular Issue.
– May 2021: Thematic Issue on Trustworthy Computing for Secure Smart Cities.
More information on the call for papers to the future thematic issues is available on the webpage of JAISE at: http://www.iospress.nl/journal/journalof-ambient-intelligence-and-smart-environments/.
T. Hu et al., Mapping urban land use by using Landsat images and Open Social data, Remote Sensing 8(2) (2016), 151. doi:10.3390/rs8020151.
J. Melià-Seguí et al., An empirical approach for fake user detection in location-based social networks, Journal of Ambient Intelligence and Smart Environments 9(6) (2017), 643–657. doi:10.3233/AIS-170464.