Evaluating indoor positioning systems in a shopping mall : the lessons learned from the IPIN 2018 competition

The Indoor Positioning and Indoor Navigation (IPIN) conference holds an annual competition in which indoor localization systems from different research groups worldwide are evaluated empirically. The objective of this competition is to establish a systematic evaluation methodology with rigorous metrics both for real-time (on-site) and post-processing (off-site) situations, in a realistic environment unfamiliar to the prototype developers. For the IPIN 2018 conference, this competition was held on September 22nd, 2018, in Atlantis, a large shopping mall in Nantes (France). Four competition tracks (two on-site and two off-site) were designed. They consisted of several 1 km routes traversing several floors of the mall. Along these paths, 180 points were topographically surveyed with a 10 cm accuracy, to serve as ground truth landmarks, combining theodolite measurements, differential global navigation satellite system (GNSS) and 3D scanner systems. 34 teams effectively competed. The accuracy score corresponds to the third quartile (75th percentile) of an error metric that combines the horizontal positioning error and the floor detection. The best results for the on-site tracks showed an accuracy score of 11.70 m (Track 1) and 5.50 m (Track 2), while the best results for the off-site tracks showed an accuracy score of 0.90 m (Track 3) and 1.30 m (Track 4). These results showed that it is possible to obtain high accuracy indoor positioning solutions in large, realistic environments using wearable light-weight sensors without deploying any beacon. This paper describes the organization work of the tracks, analyzes the methodology used to quantify the results, reviews the lessons learned from the competition and discusses its future

Multi sensor system for pedestrian tracking and activity recognition in indoor environments

The widespread use of mobile devices and the rise of Global Navigation Satellite Systems (GNSS) have allowed mobile tracking applications to become very popular and valuable in outdoor environments. However, tracking pedestrians in indoor environments with Global Positioning System (GPS)-based schemes is still very challenging. Along with indoor tracking, the ability to recognize pedestrian behavior and activities can lead to considerable growth in location-based applications including pervasive healthcare, leisure and guide services (such as, hospitals, museums, airports, etc.), and emergency services, among the most important ones. This paper presents a system for pedestrian tracking and activity recognition in indoor environments using exclusively common off-the-shelf sensors embedded in smartphones (accelerometer, gyroscope, magnetometer and barometer). The proposed system combines the knowledge found in biomechanical patterns of the human body while accomplishing basic activities, such as walking or climbing stairs up and down, along with identifiable signatures that certain indoor locations (such as turns or elevators) introduce on sensing data. The system was implemented and tested on Android-based mobile phones. The system detects and counts steps with an accuracy of 97% and 96:67% in flat floor and stairs, respectively; detects user changes of direction and altitude with 98:88% and 96:66% accuracy, respectively; and recognizes the proposed human activities with a 95% accuracy. All modules combined lead to a total tracking accuracy of 91:06% in common human motion indoor displacement

Survey of detection techniques, mathematical models and simulation software in pedestrian dynamics

The study of pedestrian dynamics has become in the latest years an increasing field of research. A relevant number of technicians have been looking for improving technologies able to detect walking people in various conditions. Several researchers have dedicated their works to model walking dynamics and general laws. Many studiers have developed interesting software to simulate pedestrian behavior in all sorts of situations and environments. Nevertheless, till nowadays, no research has been carried out to analyze all the three over-mentioned aspects. The remarked lack in literature of a complete research, pointing out the fundamental features of pedestrian detection techniques, pedestrian modelling and simulation and their tight relationships, motivates the draft of this paper. Aim of the paper is, first, to provide a schematic summary of each topic. Secondly, a more detailed description of the subjects is displayed, pointing out the advantages and disadvantages of each detection technology, the working logic of each model, outlining the inputs and the provided outputs, and the main features of the simulation software. Finally, the obtained results are summarized and discussed, in order to outline the correlation among the three explained themes