Trading Off Accuracy, Timeliness, and Uplink Usage in Online GPS Tracking

Musa, ABM; Biagioni, James; Eriksson, Jakob

doi:10.1109/tmc.2015.2457432

Cited by 7 publications

(7 citation statements)

References 23 publications

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“…Complementary to trace compression, ET algorithms, in contrast to traditional periodic triggering approaches, trigger communication only when an abnormal event (that can potentially change the state of the system) has taken place [21], [22], [23]. Event triggering is particularly useful in applications where recurrent mobility patterns exist and can be obtained utilizing and analyzing collected data via machine learning or other techniques (e.g., regression, Kalman filtering) [24]- [29].…”

Section: Related Workmentioning

confidence: 99%

Model-Adaptive Event Triggering for Monitoring Recurrent Mobility Patterns in Public Transport

et al. 2023

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Section: Related Workmentioning

confidence: 99%

Model-Adaptive Event Triggering for Monitoring Recurrent Mobility Patterns in Public Transport

et al. 2023

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“…Accurate movement predictions, in turn, will alleviate the need for continuous communication to track a particular vehicle. Consequently, as elaborated in [5], several different model-based solutions were examined in the literature in order to minimize communication and hence the energy consumption of these devices (enhancing their lifespan while at the same time preserving tracking accuracy).…”

Section: Related Workmentioning

confidence: 99%

“…Event triggering is an alternative technique that has been developed to limit communication between devices while preserving high tracking accuracy [5], [8], [9]. Several strategies to handle ET signals are proposed, as is the case in [10], while many centralized, distributed and cooperative ET architectures are examined in the literature [11]- [13].…”

Section: Related Workmentioning

confidence: 99%

Adaptive multi-model monitoring of recurrent mobility patterns

Papachristoforou

Kolios

Panayiotou

et al. 2019

2019 IEEE 5th World Forum on Internet of Things (WF-IoT)

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Multi-model event-triggering is a highly promising technique for efficient monitoring of processes where instead of continuous or even periodic triggering of events, communication and control is only applied after some event interrupt. In this work we investigate an adaptive multi-model monitoring technique whereby a local host that switches between the observed models informs remote hosts of these events which in turn adapt their predictions to reduce prediction error and minimize unnecessary triggering events and future model switching, thereby reducing energy consumption and communication bandwidth. The adaptive technique is examined under a real public transport bus service scenario, where local and remote hosts use a set of mobility models to track travel times and update their arrival schedules according to detected deviations, i.e., event interrupts.

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“…GPS applications are extensive, including cargo logistics, and public journey entrance time calculation. The energy consumption of GPS based devices has been remained a research challenge for several past years (10), (11) and some energy saving strategies have been also presented (12). One method to detect devices using GPS is through a real-time differential location system and is presented in (13).…”

Section: Introductionmentioning

confidence: 99%

“…Smart electronic devices based on IEEE 1588 protocol for GPS devices is proposed in (14). Furthermore, many GPS companies claim that their GPS devices can provide timing precision enhanced than one microsecond (12). GPS base Unmanned Aerial Vehicles (UAVs) control method base strategy is proposed in (15).…”

Section: Introductionmentioning

confidence: 99%

Cooperative GPS and Neighbors Awareness Based Device Discovery for D2D Communication in in-Band Cellular Networks

Hayat¹,

Ngah²,

Zahedi³

2018

IJET

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Device to Device (D2D) communication is a new paradigm for next-generation wireless systems to offload data traffic. A device needs to discover neighbor devices on the certain channel to initiate the D2D communication within the minimum period. A device discovery technique based on Global Positioning System (GPS) and neighbor awareness base are proposed for in-band cellular networks. This method is called network-centric approach, and it improves the device discovery efficiency, accuracy, and channel capacity. The differential code is applied to measure the signal to noise ratio of each discovered device. In the case that the signal to noise ratio (SNR) of two devices is above a specified threshold value, then these two devices are qualified for D2D communication. Two procedures are explored for device discovery; discovery by CN (core network) and eNB (evolved node B) cooperation with the help of GPS and neighbor awareness. Using 'Haversine' formula, SNR base distance is calculated. Results show an increment in the channel capacity relative to SNR obtained for each device.

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Trading Off Accuracy, Timeliness, and Uplink Usage in Online GPS Tracking

Cited by 7 publications

References 23 publications

Model-Adaptive Event Triggering for Monitoring Recurrent Mobility Patterns in Public Transport

Model-Adaptive Event Triggering for Monitoring Recurrent Mobility Patterns in Public Transport

Adaptive multi-model monitoring of recurrent mobility patterns

Cooperative GPS and Neighbors Awareness Based Device Discovery for D2D Communication in in-Band Cellular Networks

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