Az előadások anyaga - 2013 (a leginkább ajánlott linkeket a jegyzetanyagban lehet megtalálni.
Az félév első felének anyaga (Pataki Béla, illetve Györke Péter) alapvetően az előadás anyagával egyezik meg. A Györke Péter által bemutatott esettanulmányokból nem lesz kérdés a zh-n. Mindamellett az anyaga megtalálható az alábbi linken:
Szenzorhálózatok alkalmazási területei (Györke Péter pptx) [2]
További, az előadás ezen részéhez kapcsolódó irodalmak:
Szenzorfúzió (egy tananyag fejezet) [4]
Szenzorfúzió (4 gyakorló feladat) [5]
Térbeli és időbeli következtetés (egy tananyag fejezet) [6]
Időbeli következtetés (egy cikk) [7]
Tipikus (érdekes) minták felismerése idősorokban [8]
Szokatlan (kiugró) értékek, illetve az idősor viselkedésének változását jelző pontok detektálása [9]
Abnormális (tipikustól eltérő) minták felismerése heterogén idősorokban [10]
Bevezető ágensekről [11]
Az ambiens intelligenciáról [12], általános bevezető (egybe) [13], frissebb [14]
Intelligens terekről [15]
Emberi aktivítások tanulása intelligens tér adaptív szabályozásához [16]
Emberi aktivítások tanulása intelligens tér adaptív szabályozásához [17]
Berendezések [18]
Kontextus-érzékeny számítástechnika [19], rövidebb ppt + esettanulmányok [20], emlékeztető követésről [21]
Anomáliák keresése idősorokban, SAX reprezentáció [22], anomáliakeresés [23], hotsax [24]
Terv szintű aktivításfelismerés. [25]
Irodalom- és linkgyújtemény (kitekíntő, tájékoztató jellegű, a témával kapcsolatos esetleges további egyetemi munkákhoz)
(még nem hozzáférhető, felfrissítés alatt!)
Sensor fusion
Principles and Techniques for Sensor data Fusion [26]
Sensor Data Fusion for Context Aware Computing Using Dempster-Shafer Theory (PhD disszertáció) [27]
Bayesian and Dempster-Shafer fusion [28]
Sensor Fusion Using Dempster-Shafer Theory [29]
Sensor Fusion Using Dempster-Shafer Theory II: Static Weighting and Kalman Filter-like Dynamic Weighting [30]
Algebra of Dempster-Shafer evidence accumulation [31]
Ambient intelligence, intellligent spaces
The n.1 web site for Ambient Intelligence ... http://www.ambientintelligence.org/ [32]
Ambient Intelligence/ elektronikus könyv http://www.emergingcommunication.com/volume6.html [33]
Fluid Interfaces Group (formerly Ambient Intelligence Group, MIT Media Lab) http://ambient.media.mit.edu/ [34]
Smart Houses, Rooms & Appliances, AAAI Topics http://www.aaai.org/AITopics/pmwiki/pmwiki.php/AITopics/SmartHouses [35]
Seminar: Intelligent Spaces, TU Dortmund http://www.irf.tu-dortmund.de/cms/en/IS/Teaching/SS07/IntelligentSpaces/index.html [36]
Ambient-Oriented Programming, uj programozási paradigma, VUB http://prog.vub.ac.be/amop/start [37]
Ambient Intelligence Lab, CMU http://www.cmu.edu/vis/projects.html [38]
Siemens, Rest and Nursing Homes
http://www.buildingtechnologies.siemens.com/BT/GLOBAL/EN/PRODUCTS_SYSTEMS/ET/GAMMA/SOLUTIONS/Pages/solutions.aspx [39]
Journal of Ambient Intelligence and Smart Environments, http://www.iospress.nl/loadtop/load.php?isbn=18761364 [40]
PEIS Ecology - Ecology of Physically Embedded Intelligent Systems, http://aass.oru.se/~peis/frameset_page.html [41]
MIT Project Oxygen http://oxygen.lcs.mit.edu/ [42]
Aware Home http://awarehome.imtc.gatech.edu/ [43]
European Research Consortium for Informatics and Mathematics www.ercim.org [44]
Special Issue on Ambient Intelligence, ERCIM NEWS, Nr 47 Oct 2001, http://www.ercim.org/publication/Ercim_News/enw47/EN47.pdf [45]
OZONE: New Technologies and Services for Emerging Nomadic Societies, http://www.hitech-projects.com/euprojects/ozone/ [46]
EUNICA: iExtensible Universal control of Appliances intelligent household system, http://www.ercim.org/publication/Ercim_News/enw47/bielikova.html [47]
inHaus: innovation Center for the Intelligent House, Duisburg, http://www.eurescom.de/message/messageMar2003/inHaus_Duisburg.asp [48]
Living Room: Tampere University of Technology, http://www.ele.tut.fi/research/personalelectronics/projects/smart_home.htm [49]
http://www.ele.tut.fi/research/personalelectronics/projects/ekoti_03/index.htm [50]
Learning and Interactions in Proactive Spaces (LIPS), http://www.ele.tut.fi/research/personalelectronics/projects/lips.htm [51]
Wireless Wellness Monitor, VTT http://www.ercim.org/publication/Ercim_News/enw46/parkaa.html [52]
Wireless Wellness Monitor II (WWM II) Software Architecture, VTT Information Technology
http://www.vtt.fi/inf/julkaisut/muut/2002/WWM_II_SW_Architecture.pdf [53]
Adaptive House, ACHE - Adaptive Control of Home Environments http://www.cs.colorado.edu/~mozer/house/ [54]
Lessons from an Adaptive Home, http://www.cs.colorado.edu/%7Emozer/papers/reprints/smart_environments.pdf [55]
An intelligent environment must be adaptive http://www.cs.colorado.edu/%7Emozer/papers/ieee.html [56]
The neural network house: An overview http://www.cs.colorado.edu/%7Emozer/papers/nnh_overview.html [57]
The neural network house: An environment that adapts to its inhabitants, http://www.cs.colorado.edu/%7Emozer/papers/nnhadapt.html [58]
The Neurothermostat: Predictive optimal control of residential heating systems, http://www.cs.colorado.edu/%7Emozer/papers/neurothermostat.html [59]
Domotica, http://ambiente.isti.cnr.it/DomoticsLab/DomoticsCourse/Download/Rolando2005/Domotica2005.Parte6.pdf [60]
Intelligent Home http://intelligenthomes.com/ [61]
House_n: http://architecture.mit.edu/house_n/ [62]
The PlaceLab http://architecture.mit.edu/house_n/placelab.html [63]
PlaceLab: A House_n + TIAX Initiative http://architecture.mit.edu/house_n/documents/PlaceLab.pdf [64]
IBM Context Sphere environment for developing and executing context-sensitive applications, http://www.research.ibm.com/cxs/index.html [65]
CALO: Cognitive Assistant that Learns and Organizes http://caloproject.sri.com/ [66]
COGAIN: network of excellence on Communication by Gaze Interaction http://www.cogain.org/ [67]
Domotic House Gateway http://portal.acm.org/citation.cfm?id=1141730 [68]
Sougdo City: A Master Plan Inspired By The World http://www.songdo.com/default.aspx [69]
U-City, Korea Leading Global u-City http://www.koreaittimes.com/story/4371/leading-global-u-city [70]
ALADIN – Ambient Lighting Assistance for an Ageing Population http://www.ambient-lighting.eu/ [71], http://www.ambient-lighting.eu/files/aladin_presentation.pdf [72]
MavHome http://ailab.eecs.wsu.edu/mavhome/index.html [73]
University of Florida Gator-Tech Smart House http://www.icta.ufl.edu/gt.htm [74]
The Gator Tech Smart House: A Programmable Pervasive Space, Computer March 2005, http://www.icta.ufl.edu/projects/publications/helal_GTSH_IEEE_Computer_March_2005.pdf [75]
iDorm http://cswww.essex.ac.uk/Research/iieg/idorm.htm [76]
Siemens Smart Home, http://w1.siemens.com/press/en/pp_cc/2005/07_jul/sosep200502_09_(gebaeude2005)_1280976.htm [77]
http://www.buildingtechnologies.siemens.com/bt/global/en/Home/Pages/home.aspx [78]
Philips http://www.philips.hu/#/headernav/consumer/ [79]
Smart Kindergarten http://nesl.ee.ucla.edu/projects/smartkg/ [80]
KidsRoom http://vismod.media.mit.edu/vismod/demos/kidsroom/kidsroom.html [81]
iButton http://www.maxim-ic.com/products/ibutton/ [82]
X10 – offical website. http://www.x10.com/ [83]
Web sites for other smart homes and smart technology, http://www.smarthome.duke.edu/program/urls.php [84]
RoboCare: to build a multi-agent system which generates user services for human assistance, http://robocare.istc.cnr.it/ [85]
Smart House Projects http://www2.imm.dtu.dk/~cdj/SmartHouseWebSite/projects.html [86]
Taxonomy of Smart Houses http://www2.imm.dtu.dk/~cdj/SmartHouseWebSite/taxonomy.html [87]
Intelligent Houses Animated Scenarios http://www2.imm.dtu.dk/~cdj/SmartHouseWebSite/scenarios.html [88]
Key Technologies for Intelligent House Implementations, http://www2.imm.dtu.dk/~cdj/SmartHouseWebSite/technologies.html [89]
The Intelligent Room, MIT http://www.ai.mit.edu/ARCHIVE/old-projects/abstracts2000/pdf/z-mhcoen1.pdf [90]
Biosphere 2 http://en.wikipedia.org/wiki/Biosphere_2 [91], http://www.b2science.org/ [92], http://www.biospherics.org/phototour.html [93]
BIOS-3 http://en.wikipedia.org/wiki/BIOS-3 [94]
AAL-AAC-ADL
New Research Challenge Persuasive Technology to Motivate Healthy Aging [95]
Vitaphone TeleCare Infokarte [96]
The Independent LifeStyle Assistant (I.L.S.A.): Deployment Lessons Learned [97]
The Independent LifeStyle Assistant (I.L.S.A.): AI Lessons Learned [98]
User Modelling in Ambient Intelligence for Elderly and Disabled People [99]
An Ambient Assisted Living System for Telemedicine with Detection of Symptoms [100]
Activity Recognition for Context-aware Hospital Applications [101]: Issues and Opportunities for the Deployment of Pervasive Networks
The Independent LifeStyle AssistantTM (I.L.S.A.): Lessons Learned [102]
A Pervasive Computing System for the Operating Room of the Future [103]
Living Assistance Systems - An Ambient Intelligence Approach [104]
HYCARE: A Hybrid Context-Aware Reminding Framework for Elders with Mild Dementia [105]
GerAmi: Improving Healthcare Delivery in Geriatric Residences [106]
An Approach to and Evaluations of Assisted Living Systems Using Ambient Intelligence for Emergency Monitoring and Prevention [107]
The use of brain-computer interfacing for ambient intelligence [108]
Ambient Interfaces for Elderly People at Home [109]
A Living Lab for Ambient Assisted Living in the Municipality of Schwechat [110]
Audiovisual Sensing of Human Movements for Home-Care and Security in a Smart Environment [111]
Social Rhythms and Nocturnal Routines in Community Dwelling Older Adults [112]
AmI-Agents
A Component-Based Ambient Agent Model for Assessment of Driving Behaviour [113]
A Generic Topology for Ambient Intelligence [114]
A Multi-agent Approach to Controlling a Smart Environment (MavHome projekt) [115]
A Multi-dimensional Model for Task Representation and Allocation in Intelligent Environments [116]
A Policy Language for a Pervasive Computing Environment [117]
Adaptive Estimation of Emotion Generation for an Ambient Agent Model [118]
Adding Intelligence to Ubiquitous Computing Environments [119] (iDorm projekt)
Agent Patterns for Ambient Intelligence [120]
Mobile Agents for Ambient Intelligence [121]
Agents Visualization in Intelligent Environments [122]
Building Brains for Rooms: Designing Distributed Software Agents [123] (Scatterbrain projekt)
Causal Reasoning for Alert Generation in Smart Homes [124]
Creating an Ambient-Intelligence Environment Using Embedded Agents (iDorm projekt) [125]
Design Principles for Intelligent Environments [126]
Inhabited intelligent environments [127] (iDorm, iDorm-2 projekt)
Interface agents: A review of the field [128]
Learning Temporal Relations in Smart Home Data [129] (MavHome projekt)
Rascal - a Resource Manager For Multi Agent Systems In Smart Spaces [130]
Realtime Role Coordination For Ambient Intelligence (PEACH - aktiv muzeum projekt) [131]
Software Agents for Ambient Intelligence [132]
Spatiotemporal Reasoning for Smart Homes [133]
Spatio-Temporal Reasoning and Context Awareness [134]
Spatial and Temporal Reasoning for Ambient Intelligence Systems [135]
Temporal Constraints with Multiple Granularities in Smart Homes [136]
Using Interval-Based Reasoning in Smart Homes [137]
Using Event Calculus for Behaviour Reasoning and Assistance in a Smart Home [138]
Keeping the Resident in the Loop: Adapting the Smart Home to the User [139]
AmI - general
Ambient Intelligence [140]: Changing Forms of Human-Computer Interaction and their Social Implications
Ambient Intelligence. Paving the way [141] ..., COST Office, 2008
Ambient Intelligence—the Next Step for Artificial Intelligence [142]
Analysis of AmI Scenarios. Safeguards in a World of Ambient Intelligence [143] (SWAMI)
Discussion on Robin Milner’s First Computer Journal Lecture: Ubiquitous Computing: Shall We Understand It [144]?
Scenarios for Ambient Intellligence in 2010 [145], ISTAG
Threats in future AmI Applications [146]: First evidence
Fuzzy learning and control
Using FML and Fuzzy Technology in Adaptive Ambient Intelligence Environments [147]
Type-2 Fuzzy Sets for Pattern Classification: A Review [148]
Monitoring the State of a Ubiquitous Robotic System: A Fuzzy Logic Approach [149]
Design Of Fuzzy Controllers [150]
A Fuzzy Incremental Synchronous Learning Technique for Embedded-Agents Learning and Control in Intelligent Inhabited Environments (iDorm) [151]
Type-2 Fuzzy Sets Made Simple [152]
A type-2 fuzzy embedded agent to realise ambient intelligence in ubiquitous computing environments [153]
Type 2 fuzzy sets and systems. An Overview [154]
Proactive Fuzzy Control and Adaptation Methods for Smart Homes [155]
The WM Method Completed: A Flexible Fuzzy System Approach to Data Mining [156]
A Third-Generation Telecare System using Fuzzy Ambient Intelligence [157]
A Fuzzy Based Architecture for Learning Relevant Embedded Agents Associations [158]
An Intelligent Fuzzy Agent Approach for Realising Ambient Intelligence in Intelligent Inhabited Environments [159]
Generating Fuzzy Rules by Learning from Examples [160]
An Incremental Adaptive Life Long Learning Approach for Type-2 Fuzzy Embedded Agents in Ambient Intelligent Environments [161]
Idősorbányászat
HOT SAX: Efficiently Finding the Most Unusual Time Series Subsequence [162]
Experiencing SAX: a Novel Symbolic Representation of Time Series [163]
HOT SAX: Finding the Most Unusual Time Series Subsequence: Algorithms and Applications [164]
Detecting Time Series Motifs Under Uniform Scaling [165]
A Novel Bit Level Time Series Representation with Implications for Similarity Search and Clustering [166]
A Symbolic Representation of Time Series, with Implications for Streaming Algorithms [167]
Visualizing and Discovering Non-Trivial Patterns In Large Time Series Databases [168]
Probabilistic Discovery of Time Series Motifs [169]
SAX home page [170]
Context computing and management
A Location Model for Ambient Intelligence [171]
Context Driven Observation of Human Activity [172]
Explanations and Context in Ambient Intelligent Systems [173]
Location Aware Resource Management in Smart Homes [174]
Semantic-level Understanding of Human Actions and Interactions using Event Hierarchy [175]
SOUPA: Standard Ontology for Ubiquitous and Pervasive Applications [176]
Towards a Better Understanding of Context and Context-Awareness [177]
Towards an extensible context ontology for Ambient Intelligence [178]
Natural language interfaces
A Reliable Natural Language Interface to Household Appliances, IUI’03, January 12–15, 2003, Miami, Florida, USA.
Human-Computer Interaction: Overview on State of the Art, INTER. J. ON SMART SENSING AND INTELLIGENT SYSTEMS, VOL. 1, NO. 1, MARCH 2008
menu2dialog, 2nd IJCAI Workshop on KNOWLEDGE AND REASONING IN PRACTICAL DIALOGUE SYSTEMS, August 5, 2001, Seattle
Reasoning in Attempto Controlled English, Technical Report ifi-2002.01
Towards a Theory of Natural Language Interfaces to Databases, IUI ’03 Miami, Florida USA
UIML: An Appliance-Independent XML User Interface Language
Sensor Web
NASASensorweb [179]
White Paper, Creation of Specific SensorML Process Models, January 27th, 2006 (Draft), Earth System Science Cent. - NSSTC, Univ. of Alabama (UAH)
Observations and Measurements, OGC 05-087r4
OGC Sensor Web Enablement: Overview and High Level Architecture, S. Nittel, A. Labrinidis, and A. Stefanidis (Eds.): GSN 2006, LNCS 4540, pp. 175–190, 2008.
OGC Sensor Web Enablement Standards [180], Sensors & Transducers Journal, Vol.71, Issue 9, Sept 2006, pp.698-706
OpenGIS Sensor Model Language (SensorML) Implementation Specification, OGC 07-000
OpenGIS Sensor Web Enablement Architecture Document, OGC 06-021r1
OGC Sensor Alert Service Candidate Implementation Specification, OGC 06-028r3
Sensor Observation Service, OGC 05-088r1
OpenGIS Sensor Planning Service, OGC 05-089r1
Sensor Web: Open Standards Infrastructure for the Community
Tutorial I: Using SensorML to describe a Complete Weather Station, Feb 27th, 2006, Earth System Science Cent. - NSSTC, Univ. of Alabama (UAH)
Sensor Model Language (SensorML): XML-Based Language for In-situ and Remote Sensors, NIST Workshop on Data Exchange Standards at the Jobsite, May 29, 2003
Smart House
Perspectives of ambient intelligence in the home environment, Telematics and Informatics 22 (2005) 221–238
Designing a Home of the Future, Pervasive computing, April–June, 2002
How Smart are our Environments? An Updated Look at the State of the Art, Journal of Pervasive and Mobile Computing, 2007
Temporal Pattern Discovery for Anomaly Detection in a Smart Home, Proc. of the 3rd IET Int. Conf. on Intell. Environments (IE 07), Germany, Sept 2007
Mining Sensor Data in Smart Environment for Temporal Activity Prediction, ACM KDD’07, August 12–15, 2007, San Jose, California, USA
Smart Homes Can Be Smarter, J.C. Augusto and C.D. Nugent (Eds.): Designing Smart Homes, LNAI 4008, pp. 1–15, 2006.
The Role of Prediction Algorithms in the MavHome Smart Home Architecture, IEEE Wireless Communications, Dec 2002
Sensors - Devices - HCI
Accessing Ambient Intelligence through Devices with Low Computational and Communication Power
Adaptive Interfaces for Supportive Ambient Intelligence Environments, K. Miesenberger et al. (Eds.): ICCHP 2008, LNCS 5105, pp. 30–37, 2008.
Ambient Compass: One Approach to Model Spatial Relations, V.G. Duffy (Ed.): Digital Human Modeling, HCII 2009, LNCS 5620, pp. 183–191, 2009.
Ambient Intelligence and Multimodality, C. Stephanidis (Ed.): Universal Access in HCI, Part II, HCII 2007, LNCS 4555, pp. 33–42, 2007.
Ambient Intelligence: Towards Smart Appliance Ensembles, M. Hemmje et al. (Eds.): E.J. Neuhold Festschrift, LNCS 3379, pp. 261–270, 2005.
An Experience with Augmenting a Mirror as a Personal Ambient Display, S. Lee et al. (Eds.): APCHI 2008, LNCS 5068, pp. 183 – 192, 2008.
Bayesian Reasoning for Sensor Group-Queries and Diagnosis, R. Kotagiri et al. (Eds.): DASFAA 2007, LNCS 4443, pp. 522–538, 2007
Bi-Fi: An Embedded Sensor/System Architecture for Remote Biological Monitoring, IEEE Transactions on Information Technology in Biomedicine
Building a Sensor Ontology: A Practical Approach Leveraging ISO and OGC Models
End User Tools for Ambient Intelligence Environments: An Overview, Human-Computer Interaction, Part II, HCII 2007, LNCS 4551, pp. 864–872, 2007.
Engaging Personas and Narrative Scenarios, Lene Nielsen, PhD Dissertation, 2004, copenhagen business school
Fault-Tolerant Self-organization in Sensor Networks, V. Prasanna et al. (Eds.): DCOSS 2005, LNCS 3560, pp. 191–205, 2005.
Gaze as a Supplementary Modality for Interacting with Ambient Intelligence Environments, C. Stephanidis (Ed.): Universal Access in HCI, Part II, HCII 2007, LNCS 4555, pp. 848–857, 2007.
Human-Based Sensing – Sensor Systems to Complement Human Perception, Int. J. on Smart Sensing and Intell. Systems, Vol. 1, No. 1, March 2008
Human-Computer Interaction: Overview on State of the Art, Int. J. on Smart Sensing and Intell. Systems, Vol. 1, No. 1, March 2008
Hyper-Reality: Amplifying Everyday Sensory Experience
Lessons Learned Using Ubiquitous Sensors for Data Collection in Real Homes, CHI 2004, 24-29 April, Vienna, Austria
Living with Hyper-reality, Y. Cai and J. Abascal (Eds.): Ambient Intelligence in Everyday Life, LNAI 3864, pp. 130 – 141, 2006.
MULTIMODAL INTERFACES THAT PROCESS WHAT COMES NATURALLY, COMMUNICATIONS OF THE ACM March 2000/Vol. 43, No. 3
Ontology-driven Adaptive Sensor Networks
Patient Sensors: A Data Quality Perspective, S. Helal et al. (Eds.): ICOST 2008, LNCS 5120, pp. 54–61, 2008.
Routing and Data Dissemination, Self-Organizing Sensor Networks, M. Bubak et al. (Eds.): ICCS 2004, LNCS 3038, pp. 1233–1240, 2004.
Sensor networks for continuous health monitoring, BT Technology Journal, Vol 22, No 3, July 2004
Sensor networks: an overview, IEEE Potentials April/May 2003
Smart-Its Friends: A Technique for Users to Easily Establish Connections between Smart Artefacts
The Pervasive Sensor, H. Murakami et al. (Eds.): UCS 2004, LNCS 3598, pp. 1 – 9, 2005.
Planning
Problems with Intent Recognition for Elder Care [181]
Logic Programming, Abduction and Probability [182], a top-down anytime algorithm for estimating prior and posterior probabilities
Partial Observability and Probabilistic Plan/Goal Recognition [183]
Plan Recognition in Intrusion Detection Systems [184]
Plan-Based Configuration of an Ecology of Robots [185]
Probabilistic Horn abduction and Bayesian networks [186]
Probabilistic Plan Recognition for Hostile Agents [187]
Recognizing Plan/Goal Abandonment [188]
Representing diagnostic knowledge for probabilistic Horn abduction [189]
Formal theory of plan recognition and its implementation [190] (logika)
Fuzzy C-means klaszterezés ppt, wiki [191]
Kálmán-szűrők bevezetés, Kálmán R. eredeti cikke