Alfio Costanzo

GPS Sensing Systems and Fuzzy Rules to Improve Urban Navigation Assistance and Planning

Mobile navigation assistance is effective if the paths to destination are chosen taking into account the current traffic flows. Also, personal and social data dealing with the current user status/task and citizen preferences should be taken into account to suggest the most appropriate services. To this aim, the paper proposes a mobile recommending system able to suggest minimum travel time paths to destination taking into account the current traffic conditions and to recommend the services most suitable to the user needs. Such recommending system works using logic rules instead of procedural algorithms, whereas the traffic monitoring system is obtained by means of the GPS signals received from the mobiles of the users. Also, the proposal provides a way to compute the Origin Destination Matrix and to optimize the parameters of the adopted traffic simulation model to increase the model reliability in predicting if novel traffic infrastructures and policies are able to decrease the time spent in the vehicles and the gasoline consumption.

An arduino based system provided with GPS/GPRS shield for real time monitoring of traffic flows

In the past, few Public Administrations provided traffic monitoring services in real time due to the high cost of the car traffic monitoring system. The paper aims at proposing a low cost system based on the GPS signals coming from Arduino based systems to collect the traffic measurements needed to compute colored traffic map and the minimum path to the destination depending on the current position. The comparison carried between the performance of the proposed system and the one based on GPS signals coming from the user mobiles points out a higher accuracy of Arduino based tracking system. Also the system may send the user data to the main information center as anonymous messages thus satisfying the privacy requirements needed for a wide activation of such a monitoring methodology.

Mobile cyber physical systems for health care: Functions, ambient ontology and e-diagnostics

In recent decades, people, especially the older ones, try to live at home in autonomous way. For this purpose it is useful to monitor their vital signs and the home environment to activate suitable environment regulation and to send alarms to family members, medical, or hospitals, according to the criticality of the subject. The paper aims at proposing a flexible and reliable monitoring system based on embedded systems and wearable devices. The system main feature is that it allows the doctor and family members to monitor the patients at distance using their mobiles. A suitable communication with the first aid center is foreseen for a fast rescue of the patients in case of critical situations. A user model ontology is adopted so that patient and context data may be used by any diagnostic and first aid software, thus envisaging an open and interoperable health monitoring system for elderly people living at home. A diagnostic system based on fuzzy rules is proposed to support the choice of the best course of actions in case of critical health conditions.

Implementing Cyber Physical social Systems for smart cities: A semantic web perspective

Aim of the paper is to give a demonstration of the main Cyber-Physical-Systems (CPSs) and social networking facilities used to implement an ubiquitous city platform called Wi-City-Plus provided with mobile and centralized decision support systems (DSSs) taking advantage of all the data of city interest, including social data, and those sensed by networked monitoring devices. In particular, the paper adopts a semantic web approach that allow us to model such data by a suitable ontology specifically designed to support the main user scenarios in smart cities and to implement both the technical interoperability and the service integration envisaged by the CPS ideal model.

An ontological ubiquitous city information platform provided with Cyber-Physical-Social-Systems

Aim of the paper is to illustrate the methodology used to implement an ubiquitous city platform called Wi-City-Plus provided with mobile and centralized Decision Support Systems (DSSs) taking advantage of all the data of city interest, including social data, and those sensed by networked ambient Cyber-Physical-Systems (CPSs). The paper proposes to model such data by a suitable RDF ontology specifically designed to support the main user scenarios in smart cities and to implement both the technical and the service interoperability envisaged by the CPS ideal model. This ontology is obtained by reusing existing ontologies and allows the DSSs to access by SPARQL queries all the relevant data independent of the proprietary technology of the CPSs and of the DBMS adopted by the data owners. Examples derived from the pilot version of the proposed platform allows us to point out advantages and perspectives of our approach.

Real time decision support systems for mobile users in intelligent cities

Current user mobility is supported by GPS navigation systems mainly based on average traffic conditions, whereas we know that both mobility and logistics operations could be facilitated if mobile users may choose the path to destination and the loading and unloading circuits using navigators that take into account the current traffic and weather conditions. Also, personal data, such as health status and age, should be taken into account by this new generation of navigators to suggest proper mobility to users. For these reasons, the paper aims at proposing a real time decision support system (DSS) that helps mobile users to reach their destination taking into account both the main external conditions and personal constraints. In the paper we propose that such DSS operates at a semantic layer on the top of the proprietary applications so that its suggestions take into account all the city datasets, while proprietary applications may continue to carry out implementation dependent functionalities, such as communicating with mobiles, taking traffic measures, launching specific alerts. The paper not only shows how structuring such a semantic layer, but also illustrates how providing such location based services to the user mobiles using JQMobile and Flash Builder frameworks.

Integrating Real Time Traffic Data and Mobile Health Diagnosis for the Mobile User First Aid

The paper aims at illustrating how the biometric data of a mobile user, such as the heart rate or the skin perspiration, taken by commercially available systems may be stored through a Bluetooth interface on the user mobile to be processed using a simple expert system that takes into account the possible pathologies and the current activity of the users to elaborate a first health diagnosis, helping the remote medical centers to decide the equipment type in the ambulance and the doctor specialties. Also, the paper points out how integrating the traffic information taken by various technologies and from people’s perceptions is possible to compute, in real time, the travel time of each road to find the minimum path to the accident position.

Implementing a Minimum Path Finder to Favor Right Driving Behaviors in the City: Integrating Prolog Rules on the Web Server to Flash Builder Action Scripts on The Mobiles

Currently, the minimum time path finder software packages reside on the user navigators or on a main urban server, but compute the minimum paths using statistical travel times. However such paths are not always the best ones, and consequently a software is envisaged which uses the current road travel times. Since such navigational and monitoring software may cause a very high server load, the paper aims at illustrating an alternative solution obtained with driver mobiles able to compute both the services suitable for the drivers and the best current paths to reach them, with a limited intervention of the server. In particular, a distributed computing scheme consisting of a navigational and monitoring software resident on the server integrated with a navigational package implemented on the mobiles is presented. A case study clarifies how the proposed solution helps both drivers and walking people.

Towards open and interoperable information platforms for mobile users: RDF methodology and case study

The paper claims that all the databases of city interest should be taken into account by a Decision Support System (DSS) to truly inform mobile users at urban/metropolitan scale. This may be accomplished if all the relevant datasets are converted in standard RFD/XML format. However, adopting a common RDF representation of the data of city interest, also called urban data ontology, to support interoperable metropolitan information systems is not a straightforward task since it is necessary to have a data definition agreed by the community of people involved in the system. To this aim, the paper advances the proposal of developing the required data ontology using an extension of the general user model ontology (GUMO). Also, practical problems that should be solved for implementing an interoperable information platform for assisting mobile people are discussed. The first concerns how supporting the main server or the mobiles to find the servers in which the needed data are stored, whereas the other concerns how mapping on each server the data from the local format to RDF or OWL formats depending on if the system designer prefers that the data needed by the DSS are retrieved using compact SPARQL queries or ad-hoc procedures. A case study illustrates how such a system may work in practice.

Towards an Open and Interoperable Platform for Real Time Decision Making in Intelligent Cities

Current navigation systems help urban mobility and logistics by using average traffic information, although such operations are facilitated if paths to destination are chosen taking into account current traffic flows and weather conditions. Also, personal and social data dealing with the current user status/task and citizen preferences should be taken into account by the navigation software to suggest the most appropriate paths. Real time decision support systems (DSSs) may help even better the mobile users if they integrate all the information available at urban scale to provide effectively the services required by the users and if they are accessed through an open platform, i.e., by any type of mobiles. To this aim, the paper proposes a DSS based on a semantic layer put on the top of the proprietary datasets so that the suggested paths may take into account all the city datasets. Also, an open platform based on JQMobile and Flash Builder frameworks is illustrated to support the users independently on the mobile used.