The anatomy of the anyplace indoor navigation service

Abstract

The pervasiveness of smartphones is leading to the uptake of a new class of Internet-based Indoor Navigation (IIN) services, which might soon diminish the need of Satellite-based localization technologies in urban environments. These services rely on geo-location databases that store spatial models along with wireless, light and magnetic signals used to localize users and provide better power efficiency and wider coverage than predominant approaches. In this article we overview Anyplace, an open, modular, extensible and scalable navigation architecture that exploits crowdsourced Wi-Fi data to develop a novel navigation service that won several international research awards for its utility and accuracy (i.e., less than 2 meters). Our MIT-licenced open-source software stack has to this date been used by thaousands of researchers and practitioners around the globe, with the public Anyplace service reaching over 100,000 real user interactions.

A Safe, Efficient and Integrated Indoor Robotic Fleet for Logistic Applications in Healthcare and Commercial Spaces: The ENDORSE Concept

“…A fundamental problem is that there is currently no open-source platform to seamlessly integrate fingerprint measurements from different types of indoor (and robot on-board) localization technologies (e.g., Wi-Fi, BLE, UWB, etc.) [3]. Our approach will be to extend the open-source Anyplace (anyplace.cs.ucy.ac.cy) architecture with components and specialized localization algorithms, which will enable fine-grain infrastructure-free localization using Internet of Things (IoT) -enabled devices.…”

“…Our approach will be to extend the open-source Anyplace (anyplace.cs.ucy.ac.cy) architecture with components and specialized localization algorithms, which will enable fine-grain infrastructure-free localization using Internet of Things (IoT) -enabled devices. We will particularly redesign the algorithmic components necessary for indoor localization, indoor localization accuracy estimation [4], API channel optimization techniques [3], and visual analytic cues necessary to provide a rigorous Fingerprint Management Studio for crowd-sourced indoor signals. The infrastructure-less multi-robot navigation will be implemented by a software architecture that will combine ROS packages for navigation and path planning implemented onto the commercially available Robotnik (www.robotnik.eu) RB1-base as shown in Fig.…”

Towards Robust Methods for Indoor Localization using Interval Data

“…The computations are made using state-of-the-art solver pyIBex 1 . This is a set of python modules for solving nonlinear problems using Interval Arithmetic tools.…”

“…In this section we investigate ways to exploit the interval measurements data in Wi-Fi Radiomap-based indoor localization techniques such as the ones implemented in Anyplace software [1].…”

“…The omni-present availability of sensor-rich smartphones along with the fact that people spend 80-90% of their time in indoor environments has recently boosted an interest around the so called Internet-based Indoor Navigation (IIN) [1]. These comprise of indoor models, such as floor-maps and points-of-interest, along with Internet of Things (IoT)-based raw data, such as wireless, light and magnetic signals, used to localize and track mobile users and targets.…”