Overview of Indoor Positioning Technologies for Context Aware AAL Applications

Schindhelm, Corina Kim; MacWilliams, Asa

doi:10.1007/978-3-642-18167-2_19

Cited by 12 publications

(5 citation statements)

References 35 publications

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“…RSSI data produced from wearable devices is a type of data with fewer privacy concerns; it can be measured continuously and unobtrusively over long periods of time to capture real-world function and behavior in a privacy-friendly way. In indoor localisation, fingerprinting using RSSI is the typical technique used to estimate the wearable (user) location by using signal strength data representing a coarse and noisy estimate of the distance access point from the wearable [5,40]. RSSI signals are not stable, they fluctuate randomly due to shadowing, fading and multi-path effects.…”

Section: Related Workmentioning

confidence: 99%

Multimodal Indoor Localisation in Parkinson's Disease for Detecting Medication Use: Observational Pilot Study in a Free-Living Setting

Jovan

Morgan

McConville

et al. 2023

Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining

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Parkinson's disease (PD) is a slowly progressive, debilitating neurodegenerative disease which causes motor symptoms including gait dysfunction. Motor fluctuations are alterations between periods with a positive response to levodopa therapy ("on") and periods marked by re-emergency of PD symptoms ("off") as the response to medication wears off. These fluctuations often affect gait speed and they increase in their disabling impact as PD progresses. To improve the effectiveness of current indoor localisation methods, a transformer-based approach utilising dual modalities which provide complementary views of movement, Received Signal Strength Indicator (RSSI) and accelerometer data from wearable devices, is proposed. A sub-objective aims to evaluate whether indoor localisation, including its in-home gait speed features (i.e. the time taken to walk between rooms), could be used to evaluate motor fluctuations by detecting whether the person with PD is taking levodopa medications or withholding them. To properly evaluate our proposed method, we use a free-living dataset where the movements and mobility are greatly varied and unstructured as expected in real-world conditions. 24 participants lived in pairs (consisting of one person with PD, one control) for five days in a smart home with various sensors. Our evaluation on the resulting dataset demonstrates that our proposed network outperforms other methods for indoor localisation. The sub-objective evaluation shows that precise room-level localisation predictions, transformed into in-home gait speed features, produce accurate predictions on whether the PD participant is taking or withholding their medications.

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Section: Related Workmentioning

confidence: 99%

Multimodal Indoor Localisation in Parkinson's Disease for Detecting Medication Use: Observational Pilot Study in a Free-Living Setting

Jovan

Morgan

McConville

et al. 2023

Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining

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“…Sometimes the target environment restricts the design to a particular indoor positioning system (IPS) technology, directly related to accuracy, range, or scalability [ 1 , 2 , 3 , 4 , 5 ]. Indoor positioning data shall enable numerous relevant applications, such as pedestrian tracking [ 6 ]; location-based services [ 7 , 8 ] in public and commercial centers [ 9 ]; assistance services in daily activities (ambient assistant living (AAL)) [ 10 ]; location and tracking of users in geriatric and hospital centers [ 11 , 12 ]; location and tracking of emergency intervention agents (e.g., police/firefighters) [ 13 , 14 , 15 ]; location and guidance of autonomous vehicles in industrial environments and automated car parks [ 16 , 17 ]; tracking of high value goods during storage; extra information for users via augmented reality [ 18 , 19 ]; and Internet of Things (IoT) [ 20 ].…”

Section: Introductionmentioning

confidence: 99%

Weak Calibration of a Visible Light Positioning System Based on a Position-Sensitive Detector: Positioning Error Assessment

De-La-Llana-Calvo

Lázaro-Galilea

Gardel

et al. 2021

Sensors

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Reduced deployment and calibration requirements are key for scalable and cost-effective indoor positioning systems. In this work, we propose a low-complexity, weak calibration procedure for an indoor positioning system based on infrastructure lighting and a positioning-sensitive detector. The proposed calibration relies on genetic algorithms to obtain the relevant system parameters in the real positioning environment without a priori information, and requires a low number of simple measurements. The achievable performance of the proposal was assessed by direct comparison with a formal offline calibration method requiring complex dedicated infrastructure and instruments. The comparative error assessment showed that the maximum accuracy reduction compared to the significantly more costly formal calibration was below 25 mm, and the overall absolute positioning error was smaller than 35 mm with orientation errors of around 0.25°. The performance achieved with the proposed weak calibration procedure is sufficient for many indoor positioning applications and largely reduces the cost and complexity of setting up the positioning system in real environments.

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“…Different absolute positioning systems exist that use miscellaneous operating principles, such as Time-Of-Flight (TOF), Time Difference Of Arrival (TDOA), Phase Of Arrival (POA), or Received Signal Strength Indicator (RSSI) of a signal [7,8]; however, these can be generally divided according to the basic calculation principle into those using lateration and angulation-based techniques. The former utilizes the distance measurements between a set of reference points (often referred to as anchors or beacons) and the tracked object, while the latter relies on the angles measured between the object and the beacons.…”

Section: Introductionmentioning

confidence: 99%

A Novel Hybrid NN-ABPE-Based Calibration Method for Improving Accuracy of Lateration Positioning System

Petrović

Ciężkowski

Romaniuk

et al. 2021

Sensors

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Positioning systems based on the lateration method utilize distance measurements and the knowledge of the location of the beacons to estimate the position of the target object. Although most of the global positioning techniques rely on beacons whose locations are known a priori, miscellaneous factors and disturbances such as obstacles, reflections, signal propagation speed, the orientation of antennas, measurement offsets of the beacons hardware, electromagnetic noise, or delays can affect the measurement accuracy. In this paper, we propose a novel hybrid calibration method based on Neural Networks (NN) and Apparent Beacon Position Estimation (ABPE) to improve the accuracy of a lateration positioning system. The main idea of the proposed method is to use a two-step position correction pipeline that first performs the ABPE step to estimate the perceived positions of the beacons that are used in the standard position estimation algorithm and then corrects these initial estimates by filtering them with a multi-layer feed-forward neural network in the second step. In order to find an optimal neural network, 16 NN architectures with 10 learning algorithms and 12 different activation functions for hidden layers were implemented and tested in the MATLAB environment. The best training outcomes for NNs were then employed in two real-world indoor scenarios: without and with obstacles. With the aim to validate the proposed methodology in a scenario where a fast set-up of the system is desired, we tested eight different uniform sampling patterns to establish the influence of the number of the training samples on the accuracy of the system. The experimental results show that the proposed hybrid NN-ABPE method can achieve a high level of accuracy even in scenarios when a small number of calibration reference points are measured.

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Overview of Indoor Positioning Technologies for Context Aware AAL Applications

Cited by 12 publications

References 35 publications

Multimodal Indoor Localisation in Parkinson's Disease for Detecting Medication Use: Observational Pilot Study in a Free-Living Setting

Multimodal Indoor Localisation in Parkinson's Disease for Detecting Medication Use: Observational Pilot Study in a Free-Living Setting

Weak Calibration of a Visible Light Positioning System Based on a Position-Sensitive Detector: Positioning Error Assessment

A Novel Hybrid NN-ABPE-Based Calibration Method for Improving Accuracy of Lateration Positioning System

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