Journal of Ambient Intelligence and Smart Environments 12 (2020) 281–312 281 DOI 10.3233/AIS-200565 IOS Press Indexing of real time geospatial data by IoT enabled devices: Opportunities, challenges and design considerations Natalia Chaudhry a,* , Muhammad Murtaza Yousaf a and Muhammad Taimoor Khan b a PUCIT, University of the Punjab, Lahore, Pakistan E-mails: natalia@pucit.edu.pk, murtaza@pucit.edu.pk b School of Computing and Mathematical Sciences, University of Greenwich, London, UK E-mail: m.khan@gre.ac.uk Abstract. We are moving towards ‘smart’ world in which industries, such as healthcare, smart cities, transportation, and agri- culture have started using IoT (Internet of Things). These applications involve huge number of sensors and devices that generate high volume of real time data. To perform useful analytics on this data, location and spatial awareness characteristics of devices need to be considered. Wide range of location-based services and sensors in GIS have to manage moving objects that change their position with respect to time. These applications generate voluminous amount of real time geospatial data that demands an effective query processing mechanism to minimize the response time of a query. Indexing is one of the traditional ways to minimize the response time of a query by pruning the search space. In this paper, we performed a detailed survey of the liter- ature regarding the indexing of real time geospatial data generated by IoT enabled devices. Some major challenges relevant to indexing of moving objects are highlighted. Various important index design considerations are also discussed. The goal is to help researchers in understanding the principles, methods, and challenges in the indexing of real time geospatial data. This will also aid in identifying the future research opportunities. Keywords: Spatial indexing, concurrency control, GIS, Internet of things, spatiotemporal data 1. Introduction IoT characterize the future in which devices are connected to each other using the Internet and allow human-to-machine and machine-to-machine interac- tion. IoT involves large number of devices connected with each other to capture enormous amount of data. Processing this huge amount of data is a crucial as- pect in performing a valuable spatiotemporal analytics. Nowadays, idea of Bring Your Own Device (BYOD) has been propagated that has revolutionized the way devices are used. With extensive use of location-based services and sensors, geography has been inevitably linked with modern technologies. Smart building de- * Corresponding author. E-mail: natalia@pucit.edu.pk. vices, car navigation systems, and autonomous vehi- cles must be equipped with location intelligence to function properly. For example, in order for smart- phones to correctly predict the directions they must have to embed spatial awareness within them. Wide range of IoT based applications have to man- age spatial objects that change their position with re- spect to time. Examples of such objects include oil tankers, cars, and air planes. These objects are used in number of GPS and location based applications in- cluding crowd tracking, robot path planning, and traf- fic monitoring. Utilization of such spatiotemporal data plays an important role in addressing many societal is- sues. Majority of applications in the domain of trans- portation, military, agriculture, and business acquire massive amount of spatiotemporal data from sensors 1876-1364/20/$35.00 © 2020 – IOS Press and the authors. All rights reserved