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Figure: 5.1 Three Players that are bind together with the Geographic Information the players with geographic information can be visualized as shown in figure: 5.1. In the context of location based emergency services there could possibly be three main players i.e. the user (who reports the incident), the mobile operator or the wireless network provider (helps in proper communication and routing the call to the nearest emergency centre) and the emergency organization (who are responding the emergency). These emergency services must be ubiquitous for the nomadic users as termed by Yu et al., 2003c. These three players are bind together by the geographic information at each step for the user and the emergency organization (chapter-4). Similarly, for the mobile operators the geographic information helps in required for deciding the location of the transmitting towers their coverage area and the cell sizes. Binding all the players with geographic information can be visualized as shown in figure: 5.1. Assuming that the geospatial data required by the emergency services for effective and speedy response are available and is provided by the geospatial repository i.e. Indian NSDI this can be seen by setting up the whole scenario in to client server architecture as shown in figure: 5.2. Considering the actual scenario where user at the time of emergency calls the emergency number (emergency number depends up on country to country), his call is then routed to the nearest emergency control centre by the mobile operator. But, once the call is routed to the nearest ECC they might want to have access to the maps with the position of the user or the incident on to it. response are available and is provided by the geospatial repository i.e. Indian NSDI this can be

Figure 12 5.1 Three Players that are bind together with the Geographic Information the players with geographic information can be visualized as shown in figure: 5.1. In the context of location based emergency services there could possibly be three main players i.e. the user (who reports the incident), the mobile operator or the wireless network provider (helps in proper communication and routing the call to the nearest emergency centre) and the emergency organization (who are responding the emergency). These emergency services must be ubiquitous for the nomadic users as termed by Yu et al., 2003c. These three players are bind together by the geographic information at each step for the user and the emergency organization (chapter-4). Similarly, for the mobile operators the geographic information helps in required for deciding the location of the transmitting towers their coverage area and the cell sizes. Binding all the players with geographic information can be visualized as shown in figure: 5.1. Assuming that the geospatial data required by the emergency services for effective and speedy response are available and is provided by the geospatial repository i.e. Indian NSDI this can be seen by setting up the whole scenario in to client server architecture as shown in figure: 5.2. Considering the actual scenario where user at the time of emergency calls the emergency number (emergency number depends up on country to country), his call is then routed to the nearest emergency control centre by the mobile operator. But, once the call is routed to the nearest ECC they might want to have access to the maps with the position of the user or the incident on to it. response are available and is provided by the geospatial repository i.e. Indian NSDI this can be

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After setting up the technical framework, a specific use case has been identified and has been dealt in more detail. Towards the final stages of the work, the framework has been discussed in the light of the findings and finally, recommendations and conclusions have been made. Thesis Structure
After setting up the technical framework, a specific use case has been identified and has been dealt in more detail. Towards the final stages of the work, the framework has been discussed in the light of the findings and finally, recommendations and conclusions have been made. Thesis Structure
There exists abundant amount of geo-spatial data in India. A number of government organizations like Survey of India (SOD, Geological Survey of India (GSI), Department of Spac Survey of India (FSD etc. are involved in its creation, but each organization has d for the spatial data created by them. The lack of standard data format sometime data collection by different organizations thereby wasting time, effort, money, and e (DOS), Forest ifferent formats s leads to same the manpower. In order to avoid these redundancies in data collection, and to bring better coordination between different mapping agencies, a task force has been setup which is called NSDI Tas one stop portal for all the geospatial data, this task force has proposed a k force which is framework and components for it as illustrated in figure: 3.land figure: 3.2. This NSDI task force will act as a single body, which will decide, data standards, formats, specifications for the data and the database handled by the different mapping organizations (URL: 1). Source: NSDI strategy and action plan (January components for it as illustrated in figure: 3.land figure: 3.2. This NSDI task force will act as a
There exists abundant amount of geo-spatial data in India. A number of government organizations like Survey of India (SOD, Geological Survey of India (GSI), Department of Spac Survey of India (FSD etc. are involved in its creation, but each organization has d for the spatial data created by them. The lack of standard data format sometime data collection by different organizations thereby wasting time, effort, money, and e (DOS), Forest ifferent formats s leads to same the manpower. In order to avoid these redundancies in data collection, and to bring better coordination between different mapping agencies, a task force has been setup which is called NSDI Tas one stop portal for all the geospatial data, this task force has proposed a k force which is framework and components for it as illustrated in figure: 3.land figure: 3.2. This NSDI task force will act as a single body, which will decide, data standards, formats, specifications for the data and the database handled by the different mapping organizations (URL: 1). Source: NSDI strategy and action plan (January components for it as illustrated in figure: 3.land figure: 3.2. This NSDI task force will act as a
of information end user devices” (Toronen, 2003). On the first tier are the basic spatial data services, which are continuously updated by the value added service developers. Second tier utilizes the spatial data from the first tier to build the information services. “On this level different source of spatial data are possibly integrated, specific location dependent information is added, and the resulting information product is offered to the next layer in the architecture. In this process the location of the actual user, available from the applied mobile device technology, might also be made use of’. The third tier has two views it is easy to use directory services facilitating the discovery of location-based services and from the service providers vie w to adapt “the resulting service information appropriately for each category of information end user devices” (Toronen, 2003).
of information end user devices” (Toronen, 2003). On the first tier are the basic spatial data services, which are continuously updated by the value added service developers. Second tier utilizes the spatial data from the first tier to build the information services. “On this level different source of spatial data are possibly integrated, specific location dependent information is added, and the resulting information product is offered to the next layer in the architecture. In this process the location of the actual user, available from the applied mobile device technology, might also be made use of’. The third tier has two views it is easy to use directory services facilitating the discovery of location-based services and from the service providers vie w to adapt “the resulting service information appropriately for each category of information end user devices” (Toronen, 2003).
|. Technologies and the Driving Forces
|. Technologies and the Driving Forces
Figure: 4.1 Technologies and Driving Forces for the Emergency Location Services In order to tackle the above said emergencies there are certain technological driving forces that are required in emergency location services as shown in figure — 4.1. In the figure we expect user that will provide the first report of the incident, the wireless network will assist in location management based on which the GIS data sources and the real time data would be utilized for running the application. This will be further delivered to the ECC, and later the experts will analyze the extent of the damage.
Figure: 4.1 Technologies and Driving Forces for the Emergency Location Services In order to tackle the above said emergencies there are certain technological driving forces that are required in emergency location services as shown in figure — 4.1. In the figure we expect user that will provide the first report of the incident, the wireless network will assist in location management based on which the GIS data sources and the real time data would be utilized for running the application. This will be further delivered to the ECC, and later the experts will analyze the extent of the damage.
Table: 4.2 GIS Involved in Different Phases of Emergency Management 6. Geospatial Requirement in a Use Case of Fire Emergency In case of fire accident, although the fire department may respond quickly but the lack of know ledge about the location, causes, extent of the fire and traffic conditions would aggravate the situation further, which might add to the problems. Similarly, the mitigation program might get hampered where the fire vehicle even reaches the area of the fire, and lack of water further delays the response time. Thus the whole program needs to be coordinated with water supply to provide more fire hydrants, water tanks and also with the police and the medical assistance (Thapar et al, 200). situation further, which might add to the problems. Similarly, the mitigation program might get
Table: 4.2 GIS Involved in Different Phases of Emergency Management 6. Geospatial Requirement in a Use Case of Fire Emergency In case of fire accident, although the fire department may respond quickly but the lack of know ledge about the location, causes, extent of the fire and traffic conditions would aggravate the situation further, which might add to the problems. Similarly, the mitigation program might get hampered where the fire vehicle even reaches the area of the fire, and lack of water further delays the response time. Thus the whole program needs to be coordinated with water supply to provide more fire hydrants, water tanks and also with the police and the medical assistance (Thapar et al, 200). situation further, which might add to the problems. Similarly, the mitigation program might get
Table: 4.3 Identification of the data layer required from different data sources.
Table: 4.3 Identification of the data layer required from different data sources.
4.7. Filling the Gaps - In NSDI FRAMEWORK FOR LOCATION BASED EMERGENCY SERVICES IN INDIA Maintaining the data sets required in different organizations will help in sharing the information at different stages of emergency. Most d the emergencies need information related to pipelines, bui dings layouts, electrical distribution, drainage system, population and so forth. As most emergencies do not “allow time to gather these resources” (URL: 8) there exists a need for a Sys em that helps in faster information flow. Especially in the case of urban fire where fire fighters not only save the lives from fire risks but also rescue humans from building/house col hel; apse, drowning, road accident and other emergencies. Hence, sharing information not only ps maintaining interoperable data but also at the same time helps in responding to emergency fas er by taking right decisions. The interoperable systems not only improve the speed of response, but also help emergency responders to take effective measures. Maintaining the data sets required in different organizations will help in sharing the information
4.7. Filling the Gaps - In NSDI FRAMEWORK FOR LOCATION BASED EMERGENCY SERVICES IN INDIA Maintaining the data sets required in different organizations will help in sharing the information at different stages of emergency. Most d the emergencies need information related to pipelines, bui dings layouts, electrical distribution, drainage system, population and so forth. As most emergencies do not “allow time to gather these resources” (URL: 8) there exists a need for a Sys em that helps in faster information flow. Especially in the case of urban fire where fire fighters not only save the lives from fire risks but also rescue humans from building/house col hel; apse, drowning, road accident and other emergencies. Hence, sharing information not only ps maintaining interoperable data but also at the same time helps in responding to emergency fas er by taking right decisions. The interoperable systems not only improve the speed of response, but also help emergency responders to take effective measures. Maintaining the data sets required in different organizations will help in sharing the information
Figure: 4.2 Requirement Analyses for the Possible Emergency Stakeholders that can be a part of NSDI NSDI in the near future. stakeholders contributing to the emergency services must be identified, as to fill in the gap in the NSDI. Some of the main stakeholders identified are police, fire & rescue, public health department for medical services, urban planning organization etc. These organizations as shown in figure: 4.2 must come forward to develop an infrastructure that could contribute to the Indian NSDI in the near future. in figure: 4.2 must come forward to develop an infrastructure that could contribute to the Indian
Figure: 4.2 Requirement Analyses for the Possible Emergency Stakeholders that can be a part of NSDI NSDI in the near future. stakeholders contributing to the emergency services must be identified, as to fill in the gap in the NSDI. Some of the main stakeholders identified are police, fire & rescue, public health department for medical services, urban planning organization etc. These organizations as shown in figure: 4.2 must come forward to develop an infrastructure that could contribute to the Indian NSDI in the near future. in figure: 4.2 must come forward to develop an infrastructure that could contribute to the Indian
Figure: 4.3b Different Parameters and their Relations in the Hospitals Database Model.
Figure: 4.3b Different Parameters and their Relations in the Hospitals Database Model.
Figure 4.3d Different Parameters and their Relations in the Roads & Traffic Database Model FRAMEWORK FOR LOCATION BASED EMERGENCY SERVICES IN INDIA .8. User Needs From Emergency Location Services
Figure 4.3d Different Parameters and their Relations in the Roads & Traffic Database Model FRAMEWORK FOR LOCATION BASED EMERGENCY SERVICES IN INDIA .8. User Needs From Emergency Location Services
aaa Figure: 5.2 Possible client server architecture with the Routing of the Emergency Calls & Geospatial Data to the ECC (Broad view) FRAMEWORK FOR LOCATION BASED EMERGENCY SERVICES IN INDIA
aaa Figure: 5.2 Possible client server architecture with the Routing of the Emergency Calls & Geospatial Data to the ECC (Broad view) FRAMEWORK FOR LOCATION BASED EMERGENCY SERVICES IN INDIA
5.2. Framework Approach
5.2. Framework Approach
EIA receives the information along with the required geospatial data from WDA as shown in figure: 5.4d. After analyzing the data it uses time ontology agent so that the data can be sent on the basis of time. First in a standby mode it sends data to the control room manager, which initiates alarm agent. Secondly, alarm agent transfers the data to the PC on board the rescue vehicle for the on move mode. Thirdly, when the rescue team is on site they send data to the control room manager this requires a specialized agent i.e. information agent. The information agent also provides the position of the rescue vehicle to the control room manager whicl immediately sends it to the wireless domain which is then transferred to the users in that area anc when the rescue team is on site it sends the information which are essential for carrying out the damage assessment to the control room. Once the data is delivered to control room it utilizes the application agent (Aa) for carrying out the damage assessment. application agent (Aa) for carrying out the damage assessment.
EIA receives the information along with the required geospatial data from WDA as shown in figure: 5.4d. After analyzing the data it uses time ontology agent so that the data can be sent on the basis of time. First in a standby mode it sends data to the control room manager, which initiates alarm agent. Secondly, alarm agent transfers the data to the PC on board the rescue vehicle for the on move mode. Thirdly, when the rescue team is on site they send data to the control room manager this requires a specialized agent i.e. information agent. The information agent also provides the position of the rescue vehicle to the control room manager whicl immediately sends it to the wireless domain which is then transferred to the users in that area anc when the rescue team is on site it sends the information which are essential for carrying out the damage assessment to the control room. Once the data is delivered to control room it utilizes the application agent (Aa) for carrying out the damage assessment. application agent (Aa) for carrying out the damage assessment.
FRAMEWORK FOR LOCATION BASED EMERGENCY SERVICES IN INDIA
FRAMEWORK FOR LOCATION BASED EMERGENCY SERVICES IN INDIA
Figure: 5.5a Agent Interaction Diagram for the Framework -— Part |
Figure: 5.5a Agent Interaction Diagram for the Framework -— Part |
Figure: 5.5b Agent Interaction Diagram for the Framework — Part 2
Figure: 5.5b Agent Interaction Diagram for the Framework — Part 2
Figure: 5.6 Information flow in a use case of fire emergency.
Figure: 5.6 Information flow in a use case of fire emergency.
Figure: 5.7 Hierarchal Tree of the Distributed Heterogeneous Data Source for Constructing Multiple Ontologies Based on the information flow of entities in section 5.3.1 from different point of view a hierarchal tree can be constructed that helps in the identification of distributed heterogeneous sources, which further helps in the construction of multiple ontologies. This tree helps in the smooth navigation of the queries by breaking them in to number of sub-queries. As each data is not available at one node but distributed nodes. The concept of tree helps in reducing the computational load at one node, which further increases the efficiency and the speed of the system. Hence this allows bridging the gap between the user queries and the system architecture (Yu et al., 2003a).
Figure: 5.7 Hierarchal Tree of the Distributed Heterogeneous Data Source for Constructing Multiple Ontologies Based on the information flow of entities in section 5.3.1 from different point of view a hierarchal tree can be constructed that helps in the identification of distributed heterogeneous sources, which further helps in the construction of multiple ontologies. This tree helps in the smooth navigation of the queries by breaking them in to number of sub-queries. As each data is not available at one node but distributed nodes. The concept of tree helps in reducing the computational load at one node, which further increases the efficiency and the speed of the system. Hence this allows bridging the gap between the user queries and the system architecture (Yu et al., 2003a).
Figure: 5.8 Conceptual model of ontology in Emergency domain
Figure: 5.8 Conceptual model of ontology in Emergency domain
In order to process these queries mobile agents pass the query to stationary agents. These stationary agents then utilize the domain ontology as shown in figure: 5.9, to process the query based on different routing algorithm. As discussed in Shekhar et al, (2004), route should be determination based on two service the first deals with the determination of the nev route by providing input parameters like the start location, end location, optional way point: and other criteria’s like the shortest, fastest, easiest route, route for pedestrian or avoid U turns, particular street etc. the second is related to finding the new route with the minimum overlap with the existing route etc.
In order to process these queries mobile agents pass the query to stationary agents. These stationary agents then utilize the domain ontology as shown in figure: 5.9, to process the query based on different routing algorithm. As discussed in Shekhar et al, (2004), route should be determination based on two service the first deals with the determination of the nev route by providing input parameters like the start location, end location, optional way point: and other criteria’s like the shortest, fastest, easiest route, route for pedestrian or avoid U turns, particular street etc. the second is related to finding the new route with the minimum overlap with the existing route etc.
Figure: 5.10 Query Process using Facility and Route Concept Ontology
Figure: 5.10 Query Process using Facility and Route Concept Ontology
Shekhar et al, (2004), Has categorized the query on different basis like the point query, range query and the nearest neighbour query. First two queries in Table: 5.2 can be treated as the point query whereas the third can be treated as the range query. So these queries can be mathematically expressed as under: For route finding there are different algorithms available like the Dijkstra’s Algorithm (Shekhar et al, 2004), which utilizes the path length from node to node in order to compute the shortest route. Similarly the Best fit A* algorithm is based on the concept of predicted total path i.e. actual distance from initial to current node or to the target node. This algorithm is considered to be the best for finding the shortest route as it uses the semantic information from a domain. Similarly, if a user at the site of incident wants to know the nearest facility (hospital) then the query can be fired in different ways as shown in Table: 5.2.
Shekhar et al, (2004), Has categorized the query on different basis like the point query, range query and the nearest neighbour query. First two queries in Table: 5.2 can be treated as the point query whereas the third can be treated as the range query. So these queries can be mathematically expressed as under: For route finding there are different algorithms available like the Dijkstra’s Algorithm (Shekhar et al, 2004), which utilizes the path length from node to node in order to compute the shortest route. Similarly the Best fit A* algorithm is based on the concept of predicted total path i.e. actual distance from initial to current node or to the target node. This algorithm is considered to be the best for finding the shortest route as it uses the semantic information from a domain. Similarly, if a user at the site of incident wants to know the nearest facility (hospital) then the query can be fired in different ways as shown in Table: 5.2.
* Indian version of PDA, especially being made for the Indian defense forces and are now available for the civilian use. There are enormous no of handsets available in the market with the various technologies that support LBS. Some of them are given in Table below. These are the devices, through which a client can send a request to the remote server requesting for the required location base services. The requested information will be retrieved from the GIS databases depending up on the type of request from the client) and after reformatting it will be sent to the client browser application.
* Indian version of PDA, especially being made for the Indian defense forces and are now available for the civilian use. There are enormous no of handsets available in the market with the various technologies that support LBS. Some of them are given in Table below. These are the devices, through which a client can send a request to the remote server requesting for the required location base services. The requested information will be retrieved from the GIS databases depending up on the type of request from the client) and after reformatting it will be sent to the client browser application.
Technology capability — Horizontal Accuracy. (Source: CGALIES, 2002) Satellite Location Methods (Source: Toronen, 2003
Technology capability — Horizontal Accuracy. (Source: CGALIES, 2002) Satellite Location Methods (Source: Toronen, 2003
WAP is a communication protocol, which consist of relative, simple and compact version of XML, for accessing information “from micro powers running on small handheld device. WAP is based on HTML, XML and TCP/IP internet standards” and have made a WAP location framework given in fig- 5.2 (Karimi & Hammad, 2004). WAP also support the inclusion of wireless bitmap files (Wbmp). Thus it is very much possible to send a request to a geographic service through a WAP client and return the result in the form of embedded bitmap. WAP brings TCP and HTTP to mobiles, through not meant for surfing the Internet but, can be used for searching small amount of information like time table, restaurant gide etc. With the existence of WML, WAP automatically converts the visual content from HTML to WML. One of the problems with WAP is that it does not tolerate errors. Since, WML and HTML both are dialects of XML, the possibility of transferring the geographic data can be explored using this. Thus it is very much possible to send a request to a geographic service through a WAP client and
WAP is a communication protocol, which consist of relative, simple and compact version of XML, for accessing information “from micro powers running on small handheld device. WAP is based on HTML, XML and TCP/IP internet standards” and have made a WAP location framework given in fig- 5.2 (Karimi & Hammad, 2004). WAP also support the inclusion of wireless bitmap files (Wbmp). Thus it is very much possible to send a request to a geographic service through a WAP client and return the result in the form of embedded bitmap. WAP brings TCP and HTTP to mobiles, through not meant for surfing the Internet but, can be used for searching small amount of information like time table, restaurant gide etc. With the existence of WML, WAP automatically converts the visual content from HTML to WML. One of the problems with WAP is that it does not tolerate errors. Since, WML and HTML both are dialects of XML, the possibility of transferring the geographic data can be explored using this. Thus it is very much possible to send a request to a geographic service through a WAP client and
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