Project

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SwissSenseSynergy

English title SwissSenseSynergy
Applicant Braun Torsten
Number 154458
Funding scheme Sinergia
Research institution Institut für Informatik Universität Bern
Institution of higher education University of Berne - BE
Main discipline Information Technology
Start/End 01.01.2015 - 31.03.2018
Approved amount 1'100'000.00
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Keywords (8)

testbed; user-centric services; localisation; security; location based services; privacy; wireless sensor networks; social profile

Lay Summary (German)

Lead
Lokationsbasierte Dienste werden im Umfeld von mobilen Kommunikationsgeräten wie Smartphones immer wichtiger. Hieraus ergeben sich mehrere Herausforderungen. So ist es immer noch technisch anspruchsvoll den Aufenthaltsort eines Benutzers mit Hilfe der Analyse von Funksignalen sehr genau zu bestimmen, vor allem innerhalb von Gebäuden. Neben dem Ort sind für mobile Anwendungen auch andere Informationen, z.B. Umgebungsinformationen wie das aktuelle Wetter oder die Luftbelastung, interessant. Dadurch können Anwendungen unterstützt werden, die darauf basieren, Sensorinformationen von vielen mobilen Geräten zu analysieren und auszuwerten (Crowd-Sensing). Denkbar sind z.B. Verkehrsprognosen, die Messung von Umweltdaten in einem von vielen Personen abgedeckten Gebiet oder auch im Rahmen von sozialen Netzen. Andererseits steigt das Bewusstsein der Benutzer für den Datenschutz sowie die Geheimhaltung und den sicheren Umgang mit persönlichen Daten wie Aufenthaltsorte und Bewegungsmuster.
Lay summary

Ziel des Projekts ist ein Rahmenwerk zu entwickeln, welches erlaubt, in sicherer Art und Weise Lokations- oder Umgebungsdaten von Benutzern zu ermitteln, diese zu analysieren und dabei den Datenschutz zu gewährleisten. Zunächst ist es wichtig, die geographische Position eines Benutzers sowie dessen Bewegung auch innerhalb von Gebäuden mit möglichst hoher Genauigkeit zu ermitteln, z.B. um Anwendungen wie geografische Zugangskontrolle zu erlauben. Des Weiteren sollen geeignete Sensornetzstrukturen und Smartphone-Technologien identifiziert werden, die sich dazu eignen, zusätzliche Informationen über die Umgebung des Benutzers aufzunehmen. Ziel ist Crowdsensing-Anwendungen zu unterstützen, die darauf basieren, von vielen Benutzern Umgebungsinformationen (z.B. Mobilitäts- und Umweltdaten) aufzunehmen und zu verarbeiten. Mit Hilfe von in Experimentiernetzen gewonnenen Informationen ist es geplant, die Mobilität von Benutzern vorauszusagen sowie soziale und verhaltensrelevante Ähnlichkeiten und Interaktionen zwischen Personen zu ermitteln. Da es sich dabei ggf. um sensitive Informationen handelt, sind Massnahmen erforderlich, welche den Datenschutz, die Geheimhaltung und die Sicherheit der Daten gewährleisten. So sollen insbesondere Aussagen über individuelle Benutzer erschwert werden, während verlässliche Aussagen über grössere Benutzergruppen wenig beeinträchtigt werden sollen. 
Die entwickelten Mechanismen, Algorithmen und Anwendungen sollen neuartige lokationsbasierte Anwendungen, auch im Umfeld von sozialen Netzen, unterstützen, welche auf Lokations-, Mobilitäts- und Umgebungsdaten mobiler Benutzer beruhen, und gleichzeitig den Datenschutz, die Geheimhaltung und die Sicherheit der persönlichen Daten gewährleisten. 

Direct link to Lay Summary Last update: 25.09.2014

Responsible applicant and co-applicants

Employees

Publications

Publication
Real-time Smartphone Indoor Tracking Using Particle Filter with Ensemble Learning Methods
Carrera Jose, Zhao Zhongliang, Braun Torsten, Li Zan (2018), Real-time Smartphone Indoor Tracking Using Particle Filter with Ensemble Learning Methods.
Room Recognition Using Discriminative Ensemble Learning with Hidden Markov Models for Smartphones
Carrera Jose, Zhao Zhongliang, Braun Torsten (2018), Room Recognition Using Discriminative Ensemble Learning with Hidden Markov Models for Smartphones.
A Real-time Robust Indoor Tracking System in Smartphones
Carrera José, Zhao Zhongliang, Braun Torsten, Li Zan, Augusto Neto (2018), A Real-time Robust Indoor Tracking System in Smartphones, in Elsevier Journal of Computer communications, 117, 104-115.
Modelled Testbeds: Visualizing and Augmenting Physical Testbeds with Virtual Resources
Kundig Stephane, Angelopoulos Constantinos Marios, Rolim Jose (2018), Modelled Testbeds: Visualizing and Augmenting Physical Testbeds with Virtual Resources, in Proceedings of the International Conference on Information Technology & Systems (ICITS 2018), Springer International Publishing, Cham.
A Narrow-Band Indoor Positioning System by Fusing Time and Received Signal Strength via Ensemble Learning
Li Zan, Braun Torsten, Zhao Xiaohui, Zhao Zhongliang, Hu Fengye, Liang Hui (2018), A Narrow-Band Indoor Positioning System by Fusing Time and Received Signal Strength via Ensemble Learning, in IEEE Access, 6, 9936-9950.
Equilibria in Selfish Network Pricing when Paths share Resources and Users route Atomic Splittable Demand
Buwaya Julia, Rolim Jose D.P. (2018), Equilibria in Selfish Network Pricing when Paths share Resources and Users route Atomic Splittable Demand, http://www.swiss-sense-synergy.ch/, http://www.swiss-sense-synergy.ch/.
Mobile Users Location Prediction with Complex Behavior Understanding
Karimzadeh Mostafa, Zhao Zhongliang, Gerber Florian, Braun Torsten (2018), Mobile Users Location Prediction with Complex Behavior Understanding.
Social Influence (Deep) Learning for Human Behavior Prediction
Luca Luceri and Giordano Silvia and Braun Torsten (2018), Social Influence (Deep) Learning for Human Behavior Prediction, in Proceedings of the 9th Conference on Complex Networks CompleNet 2018, Springer, Cham, Boston.
VIVO: a Secure, Privacy-Preserving and Real-Time Crowd-Sensing Framework for the Internet of Things
Luceri Luca, et al. (2018), VIVO: a Secure, Privacy-Preserving and Real-Time Crowd-Sensing Framework for the Internet of Things, BORIS, Bern.
On the Social Influence in Human Behavior: Physical, Homophily, and Social Communities
Luceri Luca, Vancheri Alberto, Braun Torsten, Giordano SIlvia (2017), On the Social Influence in Human Behavior: Physical, Homophily, and Social Communities, in International Workshop on Complex Networks and their Applications.
Indoor Location for Smart Environments with Wireless Sensor and Actuator Networks
Zhao Zhongliang, Kuendig Stephane, Carrera Jose, Carron Blaise, Braun Torsten, Rolim Jose (2017), Indoor Location for Smart Environments with Wireless Sensor and Actuator Networks, in 2017 IEEE 42nd Conference on Local Computer Networks (LCN), Singapore.
Atomic Routing Mechanisms for Balance of Costs and Quality in Mobile Crowdsensing Systems
Buwaya Julia, Rolim Jose D.P. (2017), Atomic Routing Mechanisms for Balance of Costs and Quality in Mobile Crowdsensing Systems, in 13th International Conference on Distributed Computing in Sensor Systems, IEEE, IEEE.
Mobile Crowdsensing from a Selfish Routing Perspective
Buwaya Julia, Rolim Jose D. P. (2017), Mobile Crowdsensing from a Selfish Routing Perspective, in 2017 IEEE International Parallel and Distributed Processing Symposium: Workshops (IPDPSW), Lake Buena Vista, FL.
Thompson Sampling For Stochastic Bandits with Graph Feedback
Tossou Aristide, Dimitrakakis Christos, Dubhashi Devdatt (2017), Thompson Sampling For Stochastic Bandits with Graph Feedback, in AAAI 2017, AAAI, San Fransisco.
Efficient collection of sensor data via a new accelerated random walk
Angelopoulos C. M., Nikoletseas S., Patroumpa D., Raptopoulos C. (2016), Efficient collection of sensor data via a new accelerated random walk, in Concurrency and Computation: Practice and Experience, 28(6), 1796-1811.
A Distributed Algorithm Using Path Dissemination for Publish-Subscribe Communication Patterns
Kündig Stéphane, Leone Pierre, Rolim José (2016), A Distributed Algorithm Using Path Dissemination for Publish-Subscribe Communication Patterns, in ACM International Symposium MobiWac 2016, Valletta, Malta.
A Real-time Indoor Tracking System by Fusing, Inertial Sensor, Radio Signal and Floor Plan
Carrera Jose, Zhao Zhongliang, Braun Torsten, Li Zan (2016), A Real-time Indoor Tracking System by Fusing, Inertial Sensor, Radio Signal and Floor Plan, in Indoor Positioning and Indoor Navigation (IPIN), 2016 International Conference on, MadridIEEE, IEEE.
A Real-time Indoor Tracking System in Smartphones
Carrera Jose, Li Zan, Zhao Zhongliang, Braun Torsten (2016), A Real-time Indoor Tracking System in Smartphones, in Proceedings of the 19th ACM International Conference on Modeling, Analysis and Simulation of Wireles, Malta.
Bounding Distributed Energy Balancing Schemes for WSNs via Modular Subgames
Buwaya Julia, Rolim José (2016), Bounding Distributed Energy Balancing Schemes for WSNs via Modular Subgames, in IEEE International Conference on Distributed Computing in Sensor Systems (DCOSS), Washington DC, USA.
Fine-grained indoor positioning and tracking systems
Li Zan (2016), Fine-grained indoor positioning and tracking systems.
Grouping-Proof-Distance-Bounding Protocols: Keep All Your Friends Close
Karlsson Christoffer, Mitrokotsa Aikaterini (2016), Grouping-Proof-Distance-Bounding Protocols: Keep All Your Friends Close, in IEEE COMMUNICATIONS LETTERS, 20(7), 1365-1368.
HB+DB: Distance bounding meets human based authentication
Pagnin Elena, Yang Anjia, Hu Qiao, Hancke Gerhard, Mitrokotsa Aikaterini (2016), HB+DB: Distance bounding meets human based authentication, in Future Generation Computer Systems, 1.
Infer Mobility Patterns and Social Dynamics for Modelling Human Behaviour
Luceri Luca, Giordano Silvia (2016), Infer Mobility Patterns and Social Dynamics for Modelling Human Behaviour, in Proceedings of IEEE 16th International Conference on Data Mining (ICDM), BarcelonaIEEE, IEEE.
On the Differential Privacy of Bayesian Inference
Zhang Zuhe, Rubinstein Benjamin, Dimitrakakis Christos (2016), On the Differential Privacy of Bayesian Inference, in AAAI (Association for the Advancement of Artificial Intelligence) 2016.
Strategies for Wireless Recharging in Mobile Ad-Hoc Networks
Angelopoulos Constantinos, Buwaya Julia, Evangelatos Orestis, Rolim José (2016), Strategies for Wireless Recharging in Mobile Ad-Hoc Networks, in Nikoletseas Sotiris (ed.), 465.
A Passive WiFi Source Localization System based on Fine-grained Power-based Trilateration
Li Zan, Braun Torsten, Dimitrova Desislava (2015), A Passive WiFi Source Localization System based on Fine-grained Power-based Trilateration, in IEEE International Symposium on World of Wireless Mobile and Multimedia Networks (WoWMoM), BostonIEEE, IEEE.
Differentially private, multi-agent multi-armed bandits
Tossou Aristide, Dimitrakakis Christos (2015), Differentially private, multi-agent multi-armed bandits, in Proceedings of the European Workshop on Reinforcement learning 2015, Lille, France.
Fine-grained Indoor Tracking by Fusing Inertial Sensor and Physical Layer Information in WLANs
Li Zan, Burbano Danilo, Zhao Zhongliang, Carrera Jose Luis, Braun Torsten (2015), Fine-grained Indoor Tracking by Fusing Inertial Sensor and Physical Layer Information in WLANs, Technischer Bericht INF-15-004 vom 22. December 2015, Bern.
Methodology for GPS Synchronization Evaluation with High Accuracy
Li Zan, Braun Torsten, Dimitrova Desislava (2015), Methodology for GPS Synchronization Evaluation with High Accuracy, in Processing of IEEE 81st Vehicular Technology Conference (VTC’15), Glasgow.
Passively Track WiFi Users with an Enhanced Particle Filter using Power-based Ranging
Li Zan, Braun Torsten (2015), Passively Track WiFi Users with an Enhanced Particle Filter using Power-based Ranging, Technischer Bericht INF-15-005 vom 22. December 2015, Bern.
REGULA: Utilizing the Regularity of Human Mobility for Location Recommendation
Mudda Steven, Giordano Silvia (2015), REGULA: Utilizing the Regularity of Human Mobility for Location Recommendation, in International Workshop on GeoStreaming, SIGSPATIAL 2015, Seattle, USAACM, USA.
Synergistic User ↔ Context Analytics
Hossmann Andreea, Li Zan, Zhao Zhongliang, Braun Torsten, Constantinos Marios, Rolim José, Papandrea Michela, Garg Kamini, Giordano Silvia, Tossou Aristide, Dimitrakakis Christos, Mitrokotsa Aikaterini (2015), Synergistic User ↔ Context Analytics, in Proceeding of 7th International Conference covering topics in ICT Innovations, OhridSpringer, Springer.
Traversal Strategies for Wireless Power Transfer in Mobile Ad-Hoc Networks
Angelopoulos Constantinos Marios, Buwaya Julia, Evangelatos Orestis, Rolim José D. P. (2015), Traversal Strategies for Wireless Power Transfer in Mobile Ad-Hoc Networks, in Proceedings of the 18th ACM International Conference MSWiM, ACM, Cancun.
Using Distance-Bounding Protocols to Securely Verify the Proximity of Two-hop Neighbors
Pagnin Elena, Hancke Gerhard, Mitrokotsa Aikaterini (2015), Using Distance-Bounding Protocols to Securely Verify the Proximity of Two-hop Neighbors, in IEEE Communications Letters, 19(7), 1173-1176.
VIVO Testbed Implementation
Papandrea Michela, Giordano Silvia, Luceri Luca, Ferrari Alan, Mudda Steven, Garg Kamini (2015), VIVO Testbed Implementation, SUPSI, Manno, Switzerland.
Achieving privacy in the adversarial multi-armed bandit
Tossou Aristide C. Y., Dimitrakakis Christos, Achieving privacy in the adversarial multi-armed bandit, in AAAI 2017.
Algorithms for Differentially Private Multi-Armed Bandits
Tossou Aristide, Dimitrakakis Christos, Algorithms for Differentially Private Multi-Armed Bandits, in AAAI (Association for the Advancement of Artificial Intelligence) 2016.
Anonymous Online Scheduling of a Mobile Crowd
Buwaya Julia, Rolim Jose, Anonymous Online Scheduling of a Mobile Crowd, in IEEE, IEEE, IEEE.
Fine-grained Indoor Tracking by Fusing Inertial Sensor and Physical Layer Information in WLANs
Li Zan, Burbano Danilo, Zhao Zhongliang, Carrera Jose, Braun Torsten, Fine-grained Indoor Tracking by Fusing Inertial Sensor and Physical Layer Information in WLANs, in Proceeding of IEEE International Conference on Communications (ICC) 2016, Kuala Lumpur, Malaysia.
Machine Learning-based Real-Time Indoor Landmark Localization
Zhao Zhongliang, Carrera Jose, Niklaus Joel, Braun Torsten, Machine Learning-based Real-Time Indoor Landmark Localization, in International Conference on Wired/Wireless Internet Communication, Boston.
Mobile Crowd Location Prediction with Hybrid Features using Ensemble Learning
Zhao Zhongliang, Karimzadeh Mostafa, Gerber Florian, Braun Torsten, Mobile Crowd Location Prediction with Hybrid Features using Ensemble Learning.
Mobility Prediction-Assisted Over-The-Top Edge Prefetching for Hierarchical VANETs
Zhao Zhongliang, Guardalben Lucas, Karimzadeh Mostafa, Silva Jose, Braun Torsten, Sargento Susana, Mobility Prediction-Assisted Over-The-Top Edge Prefetching for Hierarchical VANETs, in IEEE Journal on Selected Areas in Communications, 1.

Collaboration

Group / person Country
Types of collaboration
HOBNET consortium Greece (Europe)
- in-depth/constructive exchanges on approaches, methods or results
- Publication
- Research Infrastructure
IoT Lab consortium Switzerland (Europe)
- in-depth/constructive exchanges on approaches, methods or results
- Publication
- Research Infrastructure
University of Aveiro Portugal (Europe)
- in-depth/constructive exchanges on approaches, methods or results
- Publication
- Research Infrastructure
- Industry/business/other use-inspired collaboration
Wisebed consortium Germany (Europe)
- in-depth/constructive exchanges on approaches, methods or results
- Publication
- Research Infrastructure

Scientific events

Active participation

Title Type of contribution Title of article or contribution Date Place Persons involved
IEEE IPIN 2016 Indoor Localization Competition Talk given at a conference Successful participation of the indoor localization competition 04.10.2016 Madrid, Spain Zhao Zhongliang; Carrera Villacrés José Luis;


Self-organised

Title Date Place
First face-to-face project meeting 07.10.2015 Lugano, Switzerland
Kick-off meeting 15.01.2015 Bern, Switzerland

Knowledge transfer events

Active participation

Title Type of contribution Date Place Persons involved
CTI training course of "Business Concept" Workshop 23.09.2016 Bern, Switzerland Zhao Zhongliang;


Communication with the public

Communication Title Media Place Year
Talks/events/exhibitions ETH Agro Food Workshop German-speaking Switzerland 2017
Talks/events/exhibitions Fascination Informatics 2017 German-speaking Switzerland 2017
Talks/events/exhibitions Nacht der Forschung 2017, Universität Bern German-speaking Switzerland 2017
Media relations: print media, online media Smarter use of mobile data Swiss National Science Foundation (SNSF) news German-speaking Switzerland 2017
Talks/events/exhibitions SWITCH WiFiMon End-User Meeting German-speaking Switzerland 2017
Talks/events/exhibitions Real-time Precise 3D Indoor Positioning German-speaking Switzerland 2016

Awards

Title Year
Fritz Kutter Award for PhD dissertation. 2016
Swisscom Innovation Award 2015 for the Bachelor Thesis of Mr. Blaise Caron titled: "A Crowd Enabled Framework for Smart Environment" 2015

Abstract

The SWISSSENSESYNERGY project aims to bring together research from closely related fields, which have recently emerged due to the proliferation of wireless computing devices. In particular, the ubiquity of smart phones as well as plans to deploy large numbers of small, local-range base stations (femto cells) creates many opportunities for synergistic computation as well as numerous privacy and security concerns. At the same time, these services are much more user-centric than traditional ones. This project aims to to develop a framework for delivering secure localisation and location-based services (LBS) to users, while optimally trading off privacy requirements with user value, network performance and reliability. The following target application scenario illustrates these requirements.Application scenario: Mobility and navigation are important for a modern lifestyle. However, current navigation applications are typically limited to a few transportation modes and miss complex environmental properties or subtle user preferences. We envision an application, where information about user preferences, transportation modes, and the environment are combined into a user-oriented navigation and recommender system. Information may include real-time traffic data, public transportation, rental vehicles, air quality, weather conditions, safety ratings and user habits. The system shall suggest places to visit, transportation modes, as well as important traffic and environmental data to city officials. Users will benefit in by improved social interactions, handling mobility more sustainably and efficiently, while preserving privacy. The scenario includes several scientific challenges and research topics, which are spread across computer science and can only be met by cooperation among the consortium of SWISSSENSESYNERGY. More precisely these include:- Localisation & prediction: Due to short range of small cell network base stations, it is important to accurately determine the locations of mobile devices, so that handover and resource allocation can be efficiently performed in the network. Localisation can provide location-based services such as traffic prediction and is crucial to extract the semantic meaning of the location to be able to predict the mobility of the user at larger time-scales.- Resource allocation & optimisation: Due to the trend of smaller (femto) network cells and high mobility of users, it is important to have lightweight algorithms for optimising network topology and allocating bandwidth appropriately. This heavily depends upon a good localisation model. - User-centric location based services & crowd-sourcing: Localisation can be combined with crowd-sourcing, where mobile users supply the service with local information e.g. to create a real-time map of traffic conditions. The main challenges are to develop models for human behaviour and preferences, to ensure privacy and the accuracy of user-supplied information.- Privacy-preservation & security: Wireless communications and crowd-sourcing raise privacy concerns, due to tracking and data collection. We aim to minimise privacy issues by developing privacy-preserving algorithms for localisation, resource allocation, prediction and crowd-sourcing. A major challenge is to combine this with mechanisms for ensuring the reliability of user-supplied information.- Social behaviour & profile of users: The system needs to generalise the model of the user to include her environment (e.g., weather or air quality), her properties, preferences and habits, but also the other people around her. Extracting this social profile, the interconnections, and similarities between people will enable a system to adapt to the user, instead of the user adapting to the system. Individual partners, responsible for one of the above mentioned research topics, will consider valuable knowledge from other partners to develop solutions addressing the identified problems in a collaborative way. The target application scenario will serve as a proof-of-concept and guideline for the whole project, while individual services and algorithms will be developed by each partner. The overall goal of SWISSSENSESYNERGY is to provide a unifying framework for secure and privacy-preserving location-based services. This is sure to lead to many innovations in the intersection of localisation, resource allocation, decision making, location-based services and privacy-preservation.
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