Contact
Name | Marcus Handte |
---|---|
Position | Senior Researcher |
Phone | +49-201-183-2803 |
Fax | +49-201-183-4176 |
marcus.handte@uni-due.de | |
Address | Schützenbahn 70 Building SA 45127 Essen |
Room | SA-121 |

Education
- 2013 – Habilitation in Computer Science from Universität Duisburg-Essen (Topic: A Framework for Context-aware Applications)
- 2009 – PhD in Natural Sciences from Universität Stuttgart (Topic: System-support for Adaptive Pervasive Applications)
- 2003 – Diplom in Computer Science from Universität Stuttgart (Specializations: Software Engineering, Distributed Systems)
- 2002 – Master of Science in Computer Science from Georgia Institute of Technology in Atlanta (Specialization: Programming Languages)
- 1997 – Abitur from Albert-Schäffle-Schule in Nürtingen (Specializations: Mathematics, Business Administration)
Employments
- Since 11.2009 Universität Duisburg-Essen, Senior Researcher (Networked Embedded Systems)
- 08.2007–10.2009 Fraunhofer IAIS, Researcher and Project Leader (Cooperating Objects)
- 08.2003–07.2007 Universität Stuttgart, Institut für Parallele und Verteilte Systeme, Researcher (Distributed Systems)
- 01.2002–07.2002 Georgia Institute of Technology, Research Assistant (Programming Languages)
- 09.2002–12.2002 T-Systems GEI GmbH, Intern, (Software Consulting)
- 07.2000–12.2000 debis Systemhaus MEB GmbH, Freelance Software Developer (Product Development)
Projects
- MOIN (BMVI, MFUND) – A Nationwide Mobility Index
- INNAMORUHR (VM NRW) – Integrated and sustainable mobility for Ruhr
- TALAKO (BMWI) – Inductive taxi charging concept for public spaces
- SMATA (BMVI, MFUND) – Smart platform for the data-driven networking of taxi and charging operations
- FAIR (BMVI, MFUND) – A user-friendly provisioning of climate and weather data
- SIMON (FP7, CIP) – Assisted Mobility for Older and Impaired Users
- GAMBAS (FP7, STREP) – Adaptive Data Acquisition, Privacy-preserving Sharing
- LIVING++ (BMWi, EraSME) – Automatic Activity Recognition, Communication
- WEBDA (BMBF, AAL) – RFID-based Object Localization and Person Tracking
- PECES (FP7, STREP) – Secure Communication, Trustworhty Context Management
- 3PC (DFG, SP1140) – Peer-based Communication and Distributed Application Configuration
Teaching
- Lecture: Net-based Applications, Universität Stuttgart, WT06/07
- Lab: Intelligent and Interactive Screens, Universität Bonn, ST08, ST09
- Lab: Web-Development with Typo3, Universität Bonn, WT07/08
- Lab: Distributed Application Development with Enterprise Java Beans, Universität Stuttgart, ST05, WT05/06
- Exercise: High Performance Networking, Universität Bonn, ST09
- Seminar: Pervasive Computing/Sensor Networks, Universität Bonn, WT07/08, ST08, WT08/09, ST09
- Lab: Microcomputer Systems, Universität Duisburg-Essen, WT09/10, ST10
- Lab: Computer Architecture, Universität Duisburg-Essen, WT10/11, WT11/12, WT12/13, WT13/14
- Project: Context Recognition with Mobile Devices, Universität Duisburg-Essen, WT09/10, ST10, WT10/11, ST11, WT11/12, ST12, WT12/13, ST13, WT13/14, WT14/15
- Project: Context Prediction, Universität Duisburg-Essen, WT13/14
- Project: Indoor Localization, Universität Duisburg-Essen, WT13/14
- Project: Augmented Reality Navigation, Universität Duisburg-Essen, ST16, ST17
- Project: Remote Rendering of Geospatial Data, Universität Duisburg-Essen, ST16/17
- Seminar: Context Recognition, Universität Duisburg-Essen, WT09/10, ST10, WT10/11, ST11, WT11/12, ST12, WT12/13, ST13, WT13/14, WT14/15, WT15/16, ST16, WT16/17
- Case Study: Location-based Services, Universität Duisburg-Essen, ST14, ST15, ST16, ST17, ST18
- Lecture: Pervasive Computing, WT15/16, WT16/17, WT17/18, WT18/19, ST19, ST20
- Project Group: Location-based Services, WT17/18
- Exercises: Programming Java, ST18, ST19, ST20
- Exercises: Programming C/C++, WT18/19, WT19/20
- Project: Android-based Robot Control, ST19
- Project Group: Crowd Sourcing of Temperature Data, WT19/20
Bachelor Theses
- Gathering and Matching of User Information Derived from Social Networks, March 2010
- A System for Inertia-based Distance Estimation using Mobile Phones, July 2012
- A System for Detecting the On-Body Placement of Mobile Phones, July 2012
- An Android-based Board Game with Board Recognition, October 2012
- A Visualization Tool for Localization Data, January 2013
- A System for the Recognition of the Mode of Transportation using Mobile Phones, January 2013
- A System for Audio-based Distributed Speaker Detection, May 2013
- A BASE Extension for Spontaneous Device Interaction using Wi-Fi Direct, July 2013
- A Framework for the Derivation of and Conflict Detection in Generic Privacy Policies from Social Networks, February 2014
- System Support for Offline Maps on Android Devices, August 2014
- A Smartphone-based Recognition System for Speed Limit Signs, August 2015
Master Theses
- A Component System for Resource-efficient Context Recognition, August 2010
- An Adaptive Protocol for Resource-efficient Data Synchronization, March 2012
- Reference-based Indoor Localization using Passive RFID Technology, April 2012
- Design and Evaluation of a Multi-modal Presence Detection System, May 2013
- An Accurate Passive WLAN-based Localization System, November 2014
- Automatic Detection of WLAN Signal Propagation Changes, January 2015
- Robust Localization of Objects using Passive RFID, March 2015
- An Extensible Engine for Adaptive Transit Routing, April 2015
- Precise Person Tracking with Active RFID, April 2015
Publications
2020 |
C. W. Frank, F. Kaspar, J. D. Keller, T. Adams, M. Felkers, B. Fischer, Marcus Handte, Pedro José Marrón, H. Paulsen, M. Neteler, J. Schiewe, M. Schuchert, C. Nickel, R. Wacker, Richard Figura: FAIR: A Project to Realize a User-Friendly Exchange of Open Weather Data. Advances in Science and Research, 17 , pp. 183–190, 2020. (Type: Journal Article | Links) @article{asr-17-183-2020, title = {FAIR: A Project to Realize a User-Friendly Exchange of Open Weather Data}, author = {C. W. Frank and F. Kaspar and J. D. Keller and T. Adams and M. Felkers and B. Fischer and Marcus Handte and Pedro José Marrón and H. Paulsen and M. Neteler and J. Schiewe and M. Schuchert and C. Nickel and R. Wacker and Richard Figura}, url = {https://asr.copernicus.org/articles/17/183/2020/}, doi = {10.5194/asr-17-183-2020}, year = {2020}, date = {2020-09-18}, journal = {Advances in Science and Research}, volume = {17}, pages = {183--190}, keywords = {}, pubstate = {published}, tppubtype = {article} } |
Peter Roch, Bijan Shahbaz Nejad, Marcus Handte, Pedro José Marrón: Systematic Optimization of Image Processing Pipelines Using GPUs. Bebis, George, Yin, Zhaozheng, Kim, Edward, Bender, Jan, Subr, Kartic, Kwon, Bum Chul, Zhao, Jian, Kalkofen, Denis, Baciu, George (Ed.): Advances in Visual Computing, pp. 633–646, Springer International Publishing, Cham, 2020, ISBN: 978-3-030-64559-5. (Type: Inproceedings | Abstract | Links) @inproceedings{image-processing-pipeline-optimization, title = {Systematic Optimization of Image Processing Pipelines Using GPUs}, author = {Peter Roch and Bijan Shahbaz Nejad and Marcus Handte and Pedro José Marrón}, editor = {George Bebis and Zhaozheng Yin and Edward Kim and Jan Bender and Kartic Subr and Bum Chul Kwon and Jian Zhao and Denis Kalkofen and George Baciu}, doi = {10.1007/978-3-030-64559-5_50}, isbn = {978-3-030-64559-5}, year = {2020}, date = {2020-10-05}, booktitle = {Advances in Visual Computing}, volume = {15}, pages = {633--646}, publisher = {Springer International Publishing}, address = {Cham}, series = {Lecture Notes in Computer Science}, abstract = {Real-time computer vision systems require fast and efficient image processing pipelines. Experiments have shown that GPUs are highly suited for image processing operations, since many tasks can be processed in parallel. However, calling GPU-accelerated functions requires uploading the input parameters to the GPU's memory, calling the function itself, and downloading the result afterwards. In addition, since not all functions benefit from an increase in parallelism, many pipelines cannot be implemented exclusively using GPU functions. As a result, the optimization of pipelines requires a careful analysis of the achievable function speedup and the cost of copying data. In this paper, we first define a mathematical model to estimate the performance of an image processing pipeline. Thereafter, we present a number of micro-benchmarks gathered using OpenCV which we use to validate the model and which quantify the cost and benefits for different classes of functions. Our experiments show that comparing the function speedup without considering the time for copying can overestimate the achievable performance gain of GPU acceleration by a factor of two. Finally, we present a tool that analyzes the possible combinations of CPU and GPU function implementations for a given pipeline and computes the most efficient composition. By using the tool on their target hardware, developers can easily apply our model to optimize their application performance systematically.}, keywords = {}, pubstate = {published}, tppubtype = {inproceedings} } Real-time computer vision systems require fast and efficient image processing pipelines. Experiments have shown that GPUs are highly suited for image processing operations, since many tasks can be processed in parallel. However, calling GPU-accelerated functions requires uploading the input parameters to the GPU's memory, calling the function itself, and downloading the result afterwards. In addition, since not all functions benefit from an increase in parallelism, many pipelines cannot be implemented exclusively using GPU functions. As a result, the optimization of pipelines requires a careful analysis of the achievable function speedup and the cost of copying data. In this paper, we first define a mathematical model to estimate the performance of an image processing pipeline. Thereafter, we present a number of micro-benchmarks gathered using OpenCV which we use to validate the model and which quantify the cost and benefits for different classes of functions. Our experiments show that comparing the function speedup without considering the time for copying can overestimate the achievable performance gain of GPU acceleration by a factor of two. Finally, we present a tool that analyzes the possible combinations of CPU and GPU function implementations for a given pipeline and computes the most efficient composition. By using the tool on their target hardware, developers can easily apply our model to optimize their application performance systematically. |
Bijan Shahbaz Nejad, Peter Roch, Marcus Handte, Pedro José Marrón: A Driver Guidance System to Support the Stationary Wireless Charging of Electric Vehicles. Bebis, George, Yin, Zhaozheng, Kim, Edward, Bender, Jan, Subr, Kartic, Kwon, Chul Bum, Zhao, Jian, Kalkofen, Denis, Baciu, George (Ed.): Advances in Visual Computing, pp. 319–331, Springer International Publishing, Cham, 2020, ISBN: 978-3-030-64559-5. (Type: Inproceedings | Abstract | Links) @inproceedings{driver-guidance-system, title = {A Driver Guidance System to Support the Stationary Wireless Charging of Electric Vehicles}, author = {Bijan Shahbaz Nejad and Peter Roch and Marcus Handte and Pedro José Marrón}, editor = {George Bebis and Zhaozheng Yin and Edward Kim and Jan Bender and Kartic Subr and Chul Bum Kwon and Jian Zhao and Denis Kalkofen and George Baciu}, doi = {10.1007/978-3-030-64559-5_25}, isbn = {978-3-030-64559-5}, year = {2020}, date = {2020-10-05}, booktitle = {Advances in Visual Computing}, volume = {15}, pages = {319--331}, publisher = {Springer International Publishing}, address = {Cham}, abstract = {Air pollution is a problem in many cities. Although it is possible to mitigate this problem by replacing combustion with electric engines, at the time of writing, electric vehicles are still a rarity in European cities. Reasons for not buying an electric vehicle are not only the high purchase costs but also the uncomfortable initiation of the charging process. A more convenient alternative is wireless charging, which is enabled by integrating an induction plate into the floor and installing a charging interface at the vehicle. To maximize efficiency, the vehicle’s charging interface must be positioned accurately above the induction plate which is integrated into the floor. Since the driver cannot perceive the region below the vehicle, it is difficult to precisely align the position of the charging interface by maneuvering the vehicle. In this paper, we first discuss the requirements for driver guidance systems that help drivers to accurately position their vehicle and thus, enables them to maximize the charging efficiency. Thereafter, we present a prototypical implementation of such a system. To minimize the deployment cost for charging station operators, our prototype uses an inexpensive off-the-shelf camera system to localize the vehicles that are approaching the station. To simplify the retrofitting of existing vehicles, the prototype uses a smartphone app to generate navigation visualizations. To validate the approach, we present experiments indicating that, despite its low cost, the prototype can technically achieve the necessary precision.}, keywords = {}, pubstate = {published}, tppubtype = {inproceedings} } Air pollution is a problem in many cities. Although it is possible to mitigate this problem by replacing combustion with electric engines, at the time of writing, electric vehicles are still a rarity in European cities. Reasons for not buying an electric vehicle are not only the high purchase costs but also the uncomfortable initiation of the charging process. A more convenient alternative is wireless charging, which is enabled by integrating an induction plate into the floor and installing a charging interface at the vehicle. To maximize efficiency, the vehicle’s charging interface must be positioned accurately above the induction plate which is integrated into the floor. Since the driver cannot perceive the region below the vehicle, it is difficult to precisely align the position of the charging interface by maneuvering the vehicle. In this paper, we first discuss the requirements for driver guidance systems that help drivers to accurately position their vehicle and thus, enables them to maximize the charging efficiency. Thereafter, we present a prototypical implementation of such a system. To minimize the deployment cost for charging station operators, our prototype uses an inexpensive off-the-shelf camera system to localize the vehicles that are approaching the station. To simplify the retrofitting of existing vehicles, the prototype uses a smartphone app to generate navigation visualizations. To validate the approach, we present experiments indicating that, despite its low cost, the prototype can technically achieve the necessary precision. |
Alexander Julian Golkowski, Marcus Handte, Peter Roch, Pedro José Marrón: Quantifying the Impact of the Physical Setup of Stereo Camera Systems on Distance Estimations. 2020 Fourth IEEE International Conference on Robotic Computing (IRC), pp. 210-217, 2020. (Type: Inproceedings | Abstract | Links) @inproceedings{9287891, title = {Quantifying the Impact of the Physical Setup of Stereo Camera Systems on Distance Estimations}, author = {Alexander Julian Golkowski and Marcus Handte and Peter Roch and Pedro José Marrón}, doi = {10.1109/IRC.2020.00041}, year = {2020}, date = {2020-01-01}, booktitle = {2020 Fourth IEEE International Conference on Robotic Computing (IRC)}, pages = {210-217}, abstract = {The ability to perceive the environment accuratelyis a core requirement for autonomous navigation. In the past,researchers and practitioners have explored a broad spectrumof sensors that can be used to detect obstacles or to recognizenavigation targets. Due to their low hardware cost and highfidelity, stereo camera systems are often considered to be aparticularly versatile sensing technology. Consequently, there hasbeen a lot of work on integrating them into mobile robots.However, the existing literature focuses on presenting theconcepts and algorithms used to implement the desired robotfunctions on top of a given camera setup. As a result, the rationaleand impact of choosing this camera setup are usually neitherdiscussed nor described. Thus, when designing the stereo camerasystem for a mobile robot, there is not much general guidancebeyond isolated setups that worked for a specific robot.To close the gap, this paper studies the impact of the physicalsetup of a stereo camera system in indoor environments. To dothis, we present the results of an experimental analysis in whichwe use a given software setup to estimate the distance to anobject while systematically changing the camera setup. Thereby,we vary the three main parameters of the physical camerasetup, namely the angle and distance between the cameras aswell as the field of view. Based on the results, we derive severalguidelines on how to choose the parameters for an application.}, keywords = {}, pubstate = {published}, tppubtype = {inproceedings} } The ability to perceive the environment accuratelyis a core requirement for autonomous navigation. In the past,researchers and practitioners have explored a broad spectrumof sensors that can be used to detect obstacles or to recognizenavigation targets. Due to their low hardware cost and highfidelity, stereo camera systems are often considered to be aparticularly versatile sensing technology. Consequently, there hasbeen a lot of work on integrating them into mobile robots.However, the existing literature focuses on presenting theconcepts and algorithms used to implement the desired robotfunctions on top of a given camera setup. As a result, the rationaleand impact of choosing this camera setup are usually neitherdiscussed nor described. Thus, when designing the stereo camerasystem for a mobile robot, there is not much general guidancebeyond isolated setups that worked for a specific robot.To close the gap, this paper studies the impact of the physicalsetup of a stereo camera system in indoor environments. To dothis, we present the results of an experimental analysis in whichwe use a given software setup to estimate the distance to anobject while systematically changing the camera setup. Thereby,we vary the three main parameters of the physical camerasetup, namely the angle and distance between the cameras aswell as the field of view. Based on the results, we derive severalguidelines on how to choose the parameters for an application. |
2019 |
Richard Figura, Frank Kaspar, Jan Keller, Till Adams, Miriam Felkers, Bernd Fischer, Marcus Handte, Pedro José Marrón, Hinrich Paulsen, Jochen Schiewe, Marvin Schuchert, Richard Wacker: FAIR – User-friendly provisioning of Climate- and Weather Data. 09.09.2019. (Type: Presentation | Abstract | Links) @misc{Figura2019b, title = {FAIR – User-friendly provisioning of Climate- and Weather Data}, author = {Richard Figura and Frank Kaspar and Jan Keller and Till Adams and Miriam Felkers and Bernd Fischer and Marcus Handte and Pedro José Marrón and Hinrich Paulsen and Jochen Schiewe and Marvin Schuchert and Richard Wacker}, editor = {European Meteorological Society}, url = {https://www.emetsoc.org/events/event/ems-annual-meeting-2019/}, year = {2019}, date = {2019-09-09}, abstract = {The quote ''Data is the new oil'' most clearly describes the increasing impact of information on our society and economy. One particularly valuable source of information in this regard is climate and weather data, which is instrumental in safeguarding of traffic and transportation, the optimisation of industries, the identification of potentials and risks of climate change and the development of corresponding adaptation and mitigation strategies. However, a correct understanding and handling of such data is often difficult for users without a meteorological background. Furthermore, processing and analysing this data is a challenging task that requires specialised software solutions and an infrastructure that is able to deal with huge data sets. This is a critical issue since almost 60% of the economic value in the EU is provided by SMEs[1], which do neither have the resources nor the knowledge to process weather and climate data efficiently. Here we present FAIR, a new research project supported by the German Federal Ministry for Transport and Digital Infrastructure (BMVI) with 2.5 Million Euros. The goal of FAIR is to simplify the information exchange between the German national meteorological service (Deutscher Wetterdienst, DWD) and the economical- and public players using exemplary applications from various areas. For this purpose, FAIR defines a set of federated micro services for processing, visualisation and analysis of meteorological data. An Infrastructure as a Service (IaaS) allows small companies (or even individuals) to access these resources on demand. Further services target the extraction of specific information from model data (such as COSMO) and the conversion of the result into common formats (like GeoJSON) or the provision of the same data in OGC compliant geoservices (such as WMS/WFS) or services defined by the W3C (like SOAP or SPARQL). Assembling these kind of micro services allows us to support different kinds of applications while, at the same time, being able to acquire data from third parties and provide it to a weather service (e.g. for data assimilation). To demonstrate the benefits of these micro services, three test scenarios are envisioned: 1) the planning of wind farms, 2) the integration of meteorological data for individual traffic routing and 3) the planning of social events, such as festivals. Three additional scenarios demonstrate data acquisition and provision by users: 1) crowdsourced sensing data coming from individual smartphones, 2) processed raster data coming from MODIS LST and 3) telemetry from airplanes. [1] https://www.iwkoeln.de/fileadmin/publikationen/2017/344566/IW-Analyse_116_2017_Europaeische_Mittelstandspolitik.pdf }, keywords = {}, pubstate = {published}, tppubtype = {presentation} } The quote ''Data is the new oil'' most clearly describes the increasing impact of information on our society and economy. One particularly valuable source of information in this regard is climate and weather data, which is instrumental in safeguarding of traffic and transportation, the optimisation of industries, the identification of potentials and risks of climate change and the development of corresponding adaptation and mitigation strategies. However, a correct understanding and handling of such data is often difficult for users without a meteorological background. Furthermore, processing and analysing this data is a challenging task that requires specialised software solutions and an infrastructure that is able to deal with huge data sets. This is a critical issue since almost 60% of the economic value in the EU is provided by SMEs[1], which do neither have the resources nor the knowledge to process weather and climate data efficiently. Here we present FAIR, a new research project supported by the German Federal Ministry for Transport and Digital Infrastructure (BMVI) with 2.5 Million Euros. The goal of FAIR is to simplify the information exchange between the German national meteorological service (Deutscher Wetterdienst, DWD) and the economical- and public players using exemplary applications from various areas. For this purpose, FAIR defines a set of federated micro services for processing, visualisation and analysis of meteorological data. An Infrastructure as a Service (IaaS) allows small companies (or even individuals) to access these resources on demand. Further services target the extraction of specific information from model data (such as COSMO) and the conversion of the result into common formats (like GeoJSON) or the provision of the same data in OGC compliant geoservices (such as WMS/WFS) or services defined by the W3C (like SOAP or SPARQL). Assembling these kind of micro services allows us to support different kinds of applications while, at the same time, being able to acquire data from third parties and provide it to a weather service (e.g. for data assimilation). To demonstrate the benefits of these micro services, three test scenarios are envisioned: 1) the planning of wind farms, 2) the integration of meteorological data for individual traffic routing and 3) the planning of social events, such as festivals. Three additional scenarios demonstrate data acquisition and provision by users: 1) crowdsourced sensing data coming from individual smartphones, 2) processed raster data coming from MODIS LST and 3) telemetry from airplanes. [1] https://www.iwkoeln.de/fileadmin/publikationen/2017/344566/IW-Analyse_116_2017_Europaeische_Mittelstandspolitik.pdf |
Marcus Handte, Pedro José Marrón, Gregor Schiele, Manuel Serrano: Adaptive Middleware for the Internet of Things - The GAMBAS Approach. River Publishers, 2019, ISBN: 9788793519787. (Type: Book | Links) @book{handter, title = {Adaptive Middleware for the Internet of Things - The GAMBAS Approach}, author = {Marcus Handte and Pedro José Marrón and Gregor Schiele and Manuel Serrano}, url = {https://www.riverpublishers.com/book_details.php?book_id=684}, doi = {https://doi.org/10.13052/rp-9788793519770}, isbn = {9788793519787}, year = {2019}, date = {2019-03-01}, publisher = {River Publishers}, series = {Series in Communication}, keywords = {}, pubstate = {published}, tppubtype = {book} } |
2018 |
Falk Brockmann, Richard Figura, Marcus Handte, Pedro José Marrón: RSSI based passive detection of persons for estimating properties of waiting lines using Bluetooth Low Energy. Proceedings of the 15th International Conference on Embedded Wireless Systems and Networks (EWSN 18), 2018. (Type: Inproceedings | ) @inproceedings{Brockmann2018, title = {RSSI based passive detection of persons for estimating properties of waiting lines using Bluetooth Low Energy}, author = {Falk Brockmann and Richard Figura and Marcus Handte and Pedro José Marrón}, year = {2018}, date = {2018-02-14}, booktitle = {Proceedings of the 15th International Conference on Embedded Wireless Systems and Networks (EWSN 18)}, keywords = {}, pubstate = {published}, tppubtype = {inproceedings} } |
Falk Brockmann, Marcus Handte, Pedro José Marròn: CutiQueue: People Counting in Waiting Lines Using Bluetooth Low Energy Based Passive Presence Detection. 14th International Conference on Intelligent Environments (IE'18), Rome, Italy, 2018. (Type: Inproceedings | ) @inproceedings{brockmann_ie18, title = {CutiQueue: People Counting in Waiting Lines Using Bluetooth Low Energy Based Passive Presence Detection}, author = {Falk Brockmann and Marcus Handte and Pedro José Marròn}, year = {2018}, date = {2018-06-22}, booktitle = {14th International Conference on Intelligent Environments (IE'18)}, address = {Rome, Italy}, keywords = {}, pubstate = {published}, tppubtype = {inproceedings} } |
2017 |
Ngewi Fet, Marcus Handte, Pedro José Marrón: Autonomous Adaptation of Indoor Localization Systems in Smart Environments. Journal of Ambient Intelligence and Smart Environments, 9 (1), pp. 7–20, 2017. (Type: Journal Article | ) @article{fet2017autonomous, title = {Autonomous Adaptation of Indoor Localization Systems in Smart Environments}, author = {Ngewi Fet and Marcus Handte and Pedro José Marrón}, year = {2017}, date = {2017-01-01}, journal = {Journal of Ambient Intelligence and Smart Environments}, volume = {9}, number = {1}, pages = {7--20}, publisher = {IOS Press}, keywords = {}, pubstate = {published}, tppubtype = {article} } |
Ngewi Fet, Marcus Handte, Pedro José Marrón: Autonomous Signal Source Displacement Detection and Recalibration of Fingerprinting-based Indoor Localization Systems. 8th International Conference on Indoor Positioning and Indoor Navigation (IPIN2017), Sapporo, Japan, 2017. (Type: Inproceedings | ) @inproceedings{fet_ipin_2017, title = {Autonomous Signal Source Displacement Detection and Recalibration of Fingerprinting-based Indoor Localization Systems}, author = {Ngewi Fet and Marcus Handte and Pedro José Marrón}, year = {2017}, date = {2017-09-18}, booktitle = {8th International Conference on Indoor Positioning and Indoor Navigation (IPIN2017)}, address = {Sapporo, Japan}, keywords = {}, pubstate = {published}, tppubtype = {inproceedings} } |