Gerald Pirkl

Collecting complex activity datasets in highly rich networked sensor environments

We deployed 72 sensors of 10 modalities in 15 wireless and wired networked sensor systems in the environment, in objects, and on the body to create a sensor-rich environment for the machine recognition of human activities. We acquired data from 12 subjects performing morning activities, yielding over 25 hours of sensor data. We report the number of activity occurrences observed during post-processing, and estimate that over 13000 and 14000 object and environment interactions occurred. We describe the networked sensor setup and the methodology for data acquisition, synchronization and curation. We report on the challenges and outline lessons learned and best practice for similar large scale deployments of heterogeneous networked sensor systems. We evaluate data acquisition quality for on-body and object integrated wireless sensors; there is less than 2.5% packet loss after tuning. We outline our use of the dataset to develop new sensor network self-organization principles and machine learning techniques for activity recognition in opportunistic sensor configurations. Eventually this dataset will be made public.

OPPORTUNITY: Towards opportunistic activity and context recognition systems

Opportunistic sensing allows to efficiently collect information about the physical world and the persons behaving in it. This may mainstream human context and activity recognition in wearable and pervasive computing by removing requirements for a specific deployed infrastructure. In this paper we introduce the newly started European research project OPPORTUNITY within which we develop mobile opportunistic activity and context recognition systems. We outline the projects objective, the approach we follow along opportunistic sensing, data processing and interpretation, and autonomous adaptation and evolution to environmental and user changes, and we outline preliminary results.

Adapting magnetic resonant coupling based relative positioning technology for wearable activitiy recogniton

We demonstrate how modulated magnetic field technology that is well established in high precision, stationary motion tracking systems can be adapted to wearable activity recognition. To this end we describe the design and implementation of a cheap (components cost about 20 Euro for the transmitter and 15 Euro for the receiver), low power (17 mA for the transmitter and 40 mA for the receiver), and easily wearable (the main size constraint are the coils which are about 25 mm3) system for tracking the relative position and orientation of body parts. We evaluate our system on two recognition tasks. On a set of 6 subtle nutrition related gestures it achieves 99.25% recognition rate compared to 94.1% for a XSense inertial device (operated calibrated, euler angle mode). On the recognition of 8 Tai Chi moves it reaches 94 % compared to 86% of an accelerometer. Combining our sensor with the accelerometer leads to 100% correct recognition (as compared to 90% when combining the accelerometer with a gyro).

Towards wearable sensing-based assessment of fluid intake

Fluid intake is an important information for many health and assisted living applications. At the same time it is inherently difficult to monitor. Existing reliable solutions require augmented drinking containers, which severely limits the applicability of such systems. In this paper we investigate two key components of an unobtrusive, wearable solution that is independent of a particular drinking container or environment.

Virtual lifeline: Multimodal sensor data fusion for robust navigation in unknown environments

We present a novel, multimodal indoor navigation technique that combines pedestrian dead reckoning (PDR) with relative position information from wireless sensor nodes. It is motivated by emergency response scenarios where no fixed or pre-deployed global positioning infrastructure is available and where typical motion patterns defeat standard PDR systems. We use RF and ultrasound beacons to periodically re-align the PDR system and reduce the impact of incremental error accumulation. Unlike previous work on multimodal positioning, we allow the beacons to be dynamically deployed (dropped by the user) at previously unknown locations. A key contribution of this paper is to show that despite the fact that the beacon locations are not known (in terms of absolute coordinates), they significantly improve the performance of the system. This effect is especially relevant when a user re-traces (parts of) the path he or she had previously travelled or lingers and moves around in an irregular pattern at single locations for extended periods of time. Both situations are common and relevant for emergency response scenarios. We describe the system architecture, the fusion algorithms and provide an in depth evaluation in a large scale, realistic experiment.

Monitoring household activities and user location with a cheap, unobtrusive thermal sensor array

We demonstrate that a cheap (30USD) small, low power 8x8 thermal sensor array can by itself provide a broad range of information relevant for human activity monitoring in home and office environments. In particular the sensor can track people with an accuracy in the range of 1m (which is sufficient to recognize activity relevant regions), detect the operation mode of various appliances such as toaster, water cooker or egg cooker and actions such as opening a refrigerator, the oven or taking a shower. While there are sensing modalities for each of the above types of information (e.g. current sensors for appliances) the fact that they can all be detected by such a simple sensor is highly relevant for practical activity recognition systems. Compared to vision (or thermal imaging systems) the system has the advantage is being less privacy invasive allowing it for example to monitor bathroom activities (as shown in one of our evaluation scenarios). The paper describes the sensor, the methods used for activity detection and the evaluation.

Resonant magnetic coupling indoor localization system

Building on previous work that introduced a novel indoor positioning concept based on magnetic resonant coupling we describe an improved system to be shown during the UBICOMP 2013 demo session. We improved the magnetic field model, implemented a particle filter for position estimation and a software suite for configuration and calibration of the system.

Hybrid Teams: Flexible Collaboration Between Humans, Robots and Virtual Agents

With the increasing capabilities of agents using Artificial Intelligence, an opportunity opens up to form team like collaboration between humans and artificial agents. This paper describes the setting-up of a Hybrid Team consisting of humans, robots, virtual characters and softbots. The team is situated in a flexible industrial production. The work presented here focuses on the central architecture and the characteristics of the team members and components. To achieve the overall team goals, several challenges have to be met to find a balance between autonomous behaviors of individual agents and coordinated teamwork.

Hybrid Teams of Humans, Robots, and Virtual Agents in a Production Setting

This video paper describes the practical outcome of the first milestone of a project aiming at setting up a so-called Hybrid Team that can accomplish a wide variety of different tasks. In general, the aim is to realize and examine the collaboration of augmented humans with autonomous robots, virtual characters and SoftBots (purely software based agents) working together in a Hybrid Team to accomplish common tasks. The accompanying video shows a customized packaging scenario and can be downloaded from http://hysociatea.dfki.de/?p=441.

mBeacon: accurate, robust proximity detection with smart phones and smart watches using low frequency modulated magnetic fields

We describe a proximity detection method that leverages the internal magnetic field sensors in smart phones and smart watches to allow reliable, robust detection of proximity to predefined regions of interest within a 30--50cm radius. For marking the regions, low cost, unobtrusive, easily deployable magnetic field beacons have been implemented. We evaluate our system in 5 different use cases in semi-naturalistic lab experiments inspired by different application domains.