This paper presents a smartphone app connected to a sensor cloud for spatio-temporal management and 3D visualization of data from ad-hoc wireless sensor networks (WSN) and Internet of Things (IoT). Many existing sensor cloud services and sensor data models do not consider usage for indoors. Although geospatial references, which consist of latitude and longitude, are often included in the data models, these are insufficient for indoor localization of wireless sensor networks. In this paper, we propose a data model for localizing sensors in indoor environment, a sensor cloud framework to manage sensor data as services in the cloud, and an app that includes and visualize sensor data in-situ with 3D visualization of sensor data on floor plans or maps. EnviS is an integrated sensor cloud and app toolkit, prototyped to evaluate this research. EnviS has been tested in three case studies: to manage environmental sensors in indoor spaces, to manage indoor tracking sensors, and to monitor vital signs from wearable wristbands.
@inproceedings{DBLP:conf/mdm/SalimPPSWS14,
author = {Flora D. Salim and
Mars Dela Pena and
Yury Petrov and
Nishant Sony and
Bo Wu and
Abdelsalam Ahmed Saad},
bibsource = {dblp computer science bibliography, https://dblp.org},
biburl = {https://dblp.org/rec/conf/mdm/SalimPPSWS14.bib},
booktitle = {IEEE 15th International Conference on Mobile Data Management, MDM
2014, Brisbane, Australia, July 14-18, 2014 - Volume 1},
doi = {10.1109/MDM.2014.47},
editor = {Arkady B. Zaslavsky and
Panos K. Chrysanthis and
Christian Becker and
Jadwiga Indulska and
Mohamed F. Mokbel and
Daniela Nicklas and
Chi-Yin Chow},
pages = {329--332},
publisher = {IEEE Computer Society},
timestamp = {Tue, 19 Nov 2019 15:07:39 +0100},
title = {EnviS Tag, Scan, View: A Location-Based App for Visualizing Spatio-temporal
Data from Sensor Cloud},
url = {https://doi.org/10.1109/MDM.2014.47},
year = {2014}
}
© 2021 Flora Salim - CRUISE Research Group.