Jonathan Frez

Using the cloud to develop applications supporting geo-collaborative Situated Learning

Situated Learning stresses the importance of the context in which learning takes place. It has been therefore frequently associated with informal learning or learning outside the classroom. Cloud technologies can play an important role supporting this type of learning, since it requires ubiquitous computing support, connectivity and access to data across various scenarios: on the field, in the classroom, at home, etc. In this paper we first present the situated learning theory and how we can take advantage of services offered by Cloud Computing to implement computer applications implementing learning activities based on this theory, providing pertinent geographical information and discussion boards. Next we propose a software architecture schema which can be used as a basis for integrating existing cloud services into new applications supporting learning activities. Then we present two examples developed with this approach with its viability and advantages. These are discussed in the concluding chapter.

Dealing with incomplete and uncertain context data in geographic information systems

There are currently a growing number of people using smartphones or tablets, thus being potentially online at every moment. There are many useful applications using peoples context data, to provide services to mobile telephony/internet subscribers. Location data is particularly interesting. These applications use location data assuming it is correct, which is sometimes not the case. In this work we propose a methodology for using incomplete/uncertain information to answer questions which include uncertainty like: “Which is the probability of finding exactly N persons within the geographic area A from time Tl to time T2?”, or “Which is the probability of having a traffic jam on street S between times Tl and T2?”. We also consider some logical constraints on the data. For instance: “Exclude counting people on the subway or inside buildings because the advertising will be on screens at open air”. Our approach uses Dempster-Shafer theory combined with an ontological definition of variable types sharing similar probabilistic behavior. The whole process and the results are explained using an example case based in one of the busiest areas of the world (the Shibuya Station in Tokyo, Japan), consisting of underground train lines, surface transportation, large avenues and shopping centers. A language to describe the fuzzy scenarios is also introduced along with an application which allows users to generate and visualize 2D and 3D suitability maps using this language.

Supporting Engineering Students Learning Wireless Network Planning Using Mobile, Positioning and Web Technologies

Teaching and learning the principles of wireless communication is a challenging issue mainly because it is difficult for students to translate the theoretical models that are commonly used in this area into practical knowledge. In order to address this challenge, we explore how to design and implement novel teaching and learning activities that integrate the principles of situated learning supported by mobile, positioning and web technologies. In this paper we present the results of our on-going efforts in this direction describing the rationale of our approach, an application supporting a learning activity designed under this approach and the outcomes of an evaluation we conducted with 28 engineering students. Obtained results show that the proposed approach offers the students new possibilities to combine theoretical and practical knowledge in a variety of collaborative situations in which mobile and web technologies played a central role.

Software platform to build geo-collaborative systems supporting design and planning

Systems supporting collaborative geo-referencing of data and information activities are increasingly being used for various purposes like urban planning, risk management, geological prospection, by engineers, city planners, policemen, firefighters, geologists, architects, etc. These systems commonly implement processes and functionalities supporting decision making as well as design and planning. The various visualization metaphors which can be applied to geo-referenced data and information on an interactive map allow their users to perform tasks and activities in an intuitive and efficient way. In order to help people in the designing and programming these kinds of applications we developed a platform implementing a core of common functionalities geo-collaborative application share, supporting collaborative work over a shared workspace displaying a map. The application developer using this platform has to program only the elements which will be placed over the map in order to instantiate a particular application. These elements can range from simple graphic labels up to complex agents implementing some behavior, generating data for a simulation and interacting with the user and other agents on the map. The paper describes this architecture and three examples of using the platform for the development of applications in field of 1) wireless network planning, 2) real time spatial data analysis from an external source, and 3) satellite image processing. Since planners must often work in the field the architecture allows the development of applications for using them in desktop as well as mobile computers.

SmartCity: Public Transportation Network Planning Based on Cloud Services, Crowd Sourcing and Spatial Decision Support Theory

Cities are growing and the number people using smartphone’s and tablets it also increasing. There are many applications that collects data from users and its context. Some of these applications are producing complete and useful databases that can be used to support some cites problems. In particular spatial planning problems like transportation network planning. In this work we presented a method to use existing crowdsourcing data and cloudservices to support a transportation network decision making process. The method is based the Dempster-Shafer Theory to combine the different sources information and to model transportation demand.

Efficient Planning of Urban Public Transportation Networks

Planning efficient public transport is a key issue in modern cities. When planning a route for a bus or the line for a tram or subway it is necessary to consider the demand of the people for this service. In this work we presented a method to use existing crowdsourcing data (like Waze and OpenStreetMap) and cloud services (like Google Maps) to support a transportation network decision making process. The method is based the Dempster-Shafer Theory to model transportation demand and uses data from Waze to provide a congestion probability and data from OpenStreetMap to provide information about location of facilities such as shops, in order to predict where people may need to start or end their trip using public transportation means. The paper also presents an example about how to use this method with real data. The example shows how to analyze the current availability of public transportation stops in order to discover its weak points.

Cooperative Work for Spatial Decision Making: An Emergencies Management Case

Geographical Information systems have been frequently used to support decision processes, especially those involving emergency management. When planning the measures in case of an emergency experts must evaluate and compare many scenarios which arise from different hypotheses about where people may be at the time of the emergency and how will they react. This work presents a tool which can help a group of experts in generating, visualizing and comparing the outcomes of the different hypotheses.

Supporting Collaborative Preparation of Emergency Plans

Effective preparedness for reacting in case of a severe emergency requires that many experts with various backgrounds evaluate the possible scenarios and come up with a single, unified plan which considers all opinions. This is a typical collaborative decision-making scenario, characterized by a process cycle involving modelling the process, defining the objectives of the decision outcome, gathering data, generating options and evaluating them according to the defined objectives. This is a decision-making scenario which requires the participation of various experts, who must evaluate and compare many scenarios. Each expert will have a partial knowledge about where people may be at the time of the emergency and how they will react. In emergency scenarios the geographical information often plays a significant importance, since plans need to consider the geography of the terrain from which the population should be evacuated, the safe areas where the population should be taken to, the ways connecting evacuations, and how the rescue teams can reach the places where the emergency occurred. This work presents a tool that can help a group of experts with various types of expertise, generate, visualize and compare the outcomes of various hypotheses. The paper also presents a real case simulation in the event of a tsunami following an earthquake at a site in northern Chile and the possibilities of evacuating people to safer zones.

Supporting Collaborative Decision Making in Geo-Collaboration Scenarios

The Geo-collaboration term is applied to collaborative activities in which data and models used by participants are strongly related to geographical locations. There are many scenarios in which Geo-collaboration is used to support a collaborative decision making process. Some of these scenarios are city planning, developing evacuations for emergencies, and developing nature protecting projects. In these situations experts with various backgrounds and knowledge contribute with their opinions and viewpoints. Ideally, the final solution should combine all these viewpoints and all specialists should agree on it. Although the literature reports about procedures for combining decision makers’ opinions whose goals might be in contradiction, there are no systems which explicitly support them to reach consensus over a final joint solution. We present a tool which supports this process by allowing experts first, to propose their individual point of view, modeled in the form of beliefs according to the Dempster-Schafer evidence theory. Then, the tool lets participants visualize all proposals, discussing and combining them in a suitable consensual way.

Supporting collaboration for smarter city planning

Computer-based collaborative tools have been proven to be effective in supporting inhabitants of cities to participate more activeley in the decisions about the development of their cities and environment. These tools are also help them to organize themselfs and react more quickly to changes in the environment enabling at the same time the broad participation of its population in the decisions about its development. An example of this situation is triggered by a new law recently issued in Chile which aims to give its population an opportunity to participate in the decision about whether a new mobile communication antenna should be placed in their neighborhood and under which circumstances. This works proposes a new example of such a tool which allows citizens to gather and display the relevant information for such circumstances.