Towards Reasoning About Context in the Presence of Uncertainty

Towards Reasoning About Context in the Presence of Uncertainty, Dan Chalmers, Naranker Dulay, Morris Sloman. In proceedings of Workshop on Advanced Context Modelling, Reasoning And Management at UbiComp 2004 Nottingham, UK, (2004)

The authors show how the relationship between real world actors (person, device, room, …) and contextual information can be formulated when uncertainty can be defined with numerical context values.

Context is not static in de nition or state – one of the properties of context is that it describes a changing relationship between users, systems and their environment. Describing these relationships is crucial in any model of context which seeks to address scenarios beyond isolated users. A key issue is the treatment of uncertainty in the relationships – the quality of the sensed context data will vary due to noisy sensors, erroneous readings, out of date data etc.

Their view of context is a set of name and value pairs. This requires that the values are typed and the possibility that the values from sensors may not be precise.

The model of values can be arranged to return a value range for a confidence level. An advantage of this approach is that a trade-off between certainty and cost (power, network load, processing time, memory use, etc) is possible where context sensing is distributed:

Sensor error (both inherent granularity and due to false readings), out of date data and poor predictions will give rise to some uncertainty about sensed context in most cases. To some extent this may be mitigated by applying fusion to multiple readings [7], but some uncertainty will remain. If an application could describe the confidence it requires in the context data, the returned value can be a value range which the context awareness system believes includes the current context within the certainty constraint. It can be expected that a higher confidence can be given to a larger range of values, while a response with a smaller range may be given if one relaxes the need to include less likely possibilities.

They present definitions of relationships which are applicable to realistic context values, using numerical and tree based unit systems with uncertain values.

Geo-collaboration

Toucan Navigate is a collaborative Geographic Information System (GIS) for users of Groove. Toucan provide:

• The ability to have entire teams seeing the same map concurrently regardless of their physical location.
• Co-editing: Team members can add, update and delete map features. The changes are shared with the rest of the team automatically.
• Team Location Awareness knowing where team members are is a requirement of almost any emergency response. The team members can broadcast their location to every other team member, securely.

The image above shows satellite imagery combined with map data. The Locations for Gabriel and John are being gathered from GPS receivers and securely disseminated with other team members in real time.

A flash animation of Toucan is also available.

Geo-Chatting

GeoChat is developed as an extension ArgMap and provides integration with IM via Jabber.

Geo-chatting is the ability to exchange text messages, geometries and georeferenced imagery with online contacts. The nice feature of geochat is that ink can be drawn has locational context. Most people will use geochat to “annotate” a map, like circling a shop or drawing a driving route. Very similar features as what we use in CatchBob!

De Vuelta en BCN

First Thesis Mind Map

First mind map for my thesis. Many questions marks, sections to trim and others to expend:

Situated Interaction on Spatial Topics

In his PhD thesis (Situated Interaction on Spatial Topics. Christian Kray (2003). PhD. thesis, DISKI series vol. 274, AKA Verlag, Berlin), Christian Kray presents a model and an implementation to handle situational interactions on spatial topics as well as several adaptation strategies to cope with common problems in real-world applications.

The interaction on spatial topics is highly important no only in the context of mobile and situated systems but also in other fields such as natural language access to maps or user interfaces. Therefore, one goal of this thesis is to develop a generic model for situated interaction on spatial topics that can be used to build real world applications. [...] In addition, we analyze typical problems that arise in the context of mobile real world applications, and point out strategies for coping with them. [...] The implementation realizing the model corresponds very closely to the structure of the model, and was put to test in a scenario of a mobile tourist guide. [...] From a user’s perspective, a mobile assistance system is not very useful, if it fails when faced with less than expected information quality.

It is an interesting work for my thesis because its seeks adaptive strategies for real world applications for spatial interaction on spatial topics:

Since the world that we live in is not a perfect one, it is quite possible that information needed in the reasoning process is simply not available, or at a lower precision than what the model requires. Consequently, building a truly helpful system for real world use means to take these issues into account. Therefore, we designed several adaptation strategies for common problems in spatial interaction on spatial topics. [...]

A frequent problem arising in the context of human-computer interaction is the unreliability of information
sources: often, sensors will not return sufficiently precise information or no information at all, network connections will fail disabling access to remote databases, and some information may be immeasurable and can only be derived over time (e. g. the user’s interests).

In addition to resource restrictions on the cognitive level (e.g. driving a car), we have seen that technical resources may also be restricted. On an abstract level, the lack of lack of information ca be addressed in several general ways:

• ignoring missing information
• accessing alternative sources
• using default values
• inferring missing information
• adapting computation
• requesting information from the user

A dead recknoning algorithm can be used in case of inferring missing positioning information, The result is a set of potential positions under the assumption that the user did not change his speed and direction.

Determination of the user’s current position can be a mix of measurements, inferences and user inputs:

Chris Kray also addresses two topics of interests: self positioning and positional information visualization:

Self positioning

In case of self localization task, the user’s goal is to learn about her current location in such a way that she is able to position herself within her current model of the world. Frequently, this is achieved by means of a you-are-here map [Richter, 2001], on which not only the user’s current position is marked (by an arrow and/or a cross) but also familiar landmarks.

Position visualization

When the precision of the positional information decreases, one way to compensate is to use other graphical means to mark the user’s position such as circles that grow with the imprecision instead of crosses (see, for example, LoL@ and REAL in 3.6 and 3.7).

The choice of implementing a real world mobile tourist guide is explained as follow:

The way we selected for our model was to build a system that realizes the theories underlying our model. This has the advantage of proving the practical relevance of our approach while allowing for a later empirical evaluation of selected parts of the system in a real-world setting.

A further reason why we favored an implementation over a purely empirical or mathematical validation was the breadth of the model. Instead of just analyzing a small subset of situated interaction on spatial topics, our goal was to design a model that covers most tasks in this realm.

MapQuest's Find Me with Explicit Position Sharing and IM

The NYT has a short article “Feeling Lost? Ask Your Cellphone Where You Are” on MapQuest Find Me, even though is is already old news. The most interesting is the plan to integrate Find ME with AOL Instant Messenger later this year and to use explicit position sharing.

James Greiner, MapQuest’s vice president and general manager, said he saw MapQuest Find Me as a tool for social networking. “MapQuest helps people find places,” Mr. Greiner said. “This helps people find places where people are at“.

Sharing location with Find Me is done in push mode. The user deliberately sends his position (no automatic update). This is a design guideline that comes out of CatchBob! also.

It handles the privacy issue pretty nicely also. The positioning is done on the device (GPS) and location information are sent via (encrypted?) SMS. It means it “virtually” does not really on one centralized server.

Geospatial Web Podcast

The New Sense of the Web is an hour-long discussion on the geospatial web. (podcast)

Nicolas wrote a transcription of the talk. Great work!

The typical bad outcomes of the geo-web (privacy and digital divide) are mentioned. However I am more interesting in the challenges in making the geospatial web more usable. That is how to make it work for people. In the industry level, the biggest challenge is to make the walled gardens in order to move towards to an interoperable geo-web. Peter Morville (Ambient Findability) thinks governments should create digital parks as they do when buying part of the land and open them up as public parks! move towards an internet of objects. Another challenge is to make the technologies used by the geo-web work. Peter mentions a wifi watch with a built-in gps to track the location of your child (berk!) and that people complain because it does not work good enough. Another challenge is to manage the relation with (on and off modes) the geo-web. One caller, a trucker, complained about how being tracked during his job changed his relation with his nap time: “Everybody know where I am and what I am doing, it’s terrible. before I could take a nap without any problems (it was me and my nap) and now… it’s impossible (how come you’re not moving?)”.

Mike Liebhold mentions way to provide access to geospatial information to the less priviledge people:

There are lots of wonderful standards for a while to make information available (since gore) but about equity and access, it turned out that the cell phone is the world’s computer: if cell phone are equiped with wifi access, then you don’t necessarily have to dial to a commercial access: wifi can give you location information and access to the web in a way that it does not cost money and it does not necessarily give your location. this device will be cheap enough that less privileged people can have access to geospatial information.

I am always surprise to see WiFi as a mean to provide free access to people. WiFi (or any other current wireless service) availability far from ubiquitous, its accessibility is rarely free (outside of Montain View, Palo Alto, …). Plus, the wide and chaotic development of WiFi might lead to unpredictable degradation in coverage and data speeds and drives a need for continual network upgrades (which would be excellent for my thesis! ).

Seemyroad.com

Seemyroad.com mixes high the Google satellite maps of the Zürich area with road movies and flybys. On service is to explore the city with filmed tours or by flying over a tram line. It uses Google Maps. A proof of concept of how to animate Google Maps.

They have a funny service: “Email a streename to use and we will film it and show it here…. gratis!”

Via Cartography: Zürich Maps, Movies & FlyBys

Immo.beta.search.ch

Immo.beta.search.ch est la version suisse de projets d’intégrations de données immobilières aux cartes sur le web (geospatial web) du style Neighborhood Project, Vivirama et autres. Search.ch intégre déjà très bien les données des transports publiques à leurs cartes intéractives. Plus à lire sur le blog de Bernhard Seefeld, ancien CTO de search.ch: New AJAX Swiss Real Estate Search.

Update: A New York, PropertyShark offre, en plus des informations sur les logements, des couches cartographiques comme les zones inondables, taxation, les projets en développement. Cela peut devenir encore plus intéressant avec l’intégration des données du bruit du trafic, de préférences politiques, de connectivité par l’intermédiaire de cartogramme, ou des autres critères subjectifs de qualité de vie avec un outil pour “tuner” et visualizer les variables.

De même manière que QDQ à Barcelone, PropertyShark a photographié les 40’000 bâtiments de Manhattan.

via Pascal Rossini: Un site Suisse en Ajax et Web 2.0.