Environmental Scenario
4.2 Environmental Scenario
The following sections introduce a new area of application. However, as already explained, this area – the environmental layer – is related to the mobility scenario due to composition of the consortium and the sources of information that it is able to tap in.
Thus, most of the uses cases described hereafter rely on the data being captured from EMT Public Transport Exploitation System. Nevertheless, the different pollution levels could also be obtained from other sources as the municipality environmental sensing stations. Whenever it has been possible, the description of the use case has been kept independent to the origin of data, making the environmental scenario as independent to the mobility one as possible.
4.2.1 Use Case 01E: Running with a Friend
Use case Id
UC01E
Title
Running with a friend
Involved building blocks
Discovery Service, Processing System,
Transport System,
Environmental System
Involved applications
GAMBAS mobile application
Required data Desired destination, routes, incidents, ETA, position of people, friend relationship, levels of pollution
Offered services Adaptive trip plan based on pollution levels, notifications on when to start the trip and incidents on route, position of friends.
Involved partners
UDE, ETRA I+D, NUIG, OU, EMT
Table 11 – Running with a Friend Summary
This use case describes the use of the GAMBAS framework to design the less polluted jogging route and share it with another user.
The trigger action is a user trying to design a circular route for jogging in the less polluted and quieter area of the city. The user will query the environmental map of the city and select the intermediate points to design the route. It would also like to share this route with a friend who lives in another part of town in order to run parts of the route together.
GAMBAS mobile application must be able to share routes between users via the privacy framework and calculate common route segments or meeting points. Moreover, sharing the position of users with a specific trust relationship should infer estimated meeting points, as well as trigger proximity alerts of static or dynamic POIs – i.e. in this case the point of interest would be friends nearby.
The use of the transportation system, must be considered exclusively as an add-on to enable a sort of intermodal trip – i.e. bus and jogging – to enable users to share some time together while running.
Gambas App Gambas App
Discovery Service
Processing System
Transport System
Environment System
Registre data service Registre service
Select info layers
Registre data service
Discover data services for city Public data
Discover data services for city announcement
Query environmental data (OQP)
Query route with selected intermediate points (OQP) Protected route data announcement Protected route data announcement Discover data friend Query share location Stream query estimate meeting width friend
Get current route Get current route Stream query location
Update time meeting
Figure 11 – Running with a Friend Sequence Diagram
4.2.2 Use Case 02E: Pollution Map (Noise, Pollen and CO2 from Bus Sensors)
Use case Id
UC02E
Title Pollution map (noise, pollen and CO2 from bus sensors) Involved building blocks
Environmental System
Involved applications
Environmental application
Required data Noise, pollen and CO2 levels, position of bus and time Offered services
Pollution map of the city
Involved partners
UDE, ETRA I+D, NUIG, EMT
Table 12 – Pollution Map (Noise, Pollen and CO2 from Bus Sensors) Summary
This use case describes how to obtain a map of pollution (C02, noise and pollen) from the city public bus network.
The GAMBAS framework proposes that public transport buses as well as smartphones can serve as sensors gathering information on the environment of a Smart City. Buses in Madrid will be equipped with sensors for measuring C02, pollen and environmental noise. These sensors will be connected to an embedded piece of hardware already deployed in the buses: EFISAE. This equipment – awarded at The GAMBAS framework proposes that public transport buses as well as smartphones can serve as sensors gathering information on the environment of a Smart City. Buses in Madrid will be equipped with sensors for measuring C02, pollen and environmental noise. These sensors will be connected to an embedded piece of hardware already deployed in the buses: EFISAE. This equipment – awarded at
Figure 12 – Basic Hardware to Capture Environmental Data in Buses
As a first step, the EFISAE firmware will be adapted to connect to the new sensors. This information will be processed by the on-board control unit in each bus (BIT) in charge of communication, positioning and ticketing. This unit will feed the environmental system with the retrieved information, positioning and timing. Finally, an environmental application will process the data in order to build environmental pollution maps and offer them in the Internet.
EFISAE
BIT
Environment System
Environment App
Capture Co2 Capture Pollen
Request Env Data
Capture Noise (FFT )
process noise
Update geocoded env. data
Figure 13 – Pollution Map (Noise, Pollen and CO2 from Bus Sensors) Sequence Diagram
4.2.3 Use Case 02.1E: Pollution Map (Noise Detected by Mobile Devices)
Use case Id
UC02.1E
Title
Pollution map (noise detected by mobile devices)
Involved building blocks Discovery Service, Processing System, Environmental System Involved applications
GAMBAS mobile application
Required data
Position of people, levels of noise
Offered services
Noise map
Involved partners
UDE, ETRA I+D, NUIG, OU
Table 13 – Pollution Map (Noise Detected by Mobile Devices) Summary
If the user agrees in the privacy settings to record noise levels on the path through town, the data will be shared to create a noise profile of the city. The noise information in combination with the location and time of the day will be used to create a time depending map of noise levels within the city. This information can be used directly for the selection of jogging routes. The pollution map can also be used by the city government to identify suitable locations for child care centers or retirement homes.
GAMBAS App
Discovery Service
Processing System
Environment System
Register system
Ask user for collaboration
Register system
Query for noise level server
Send query result
Lookup Environment System
Capture noise level, location and time
Loop
Send noise updates
Forward update
Updated time depend noise level map of the city
Figure 14 – Pollution Map (Noise Detected by Mobile Devices) Sequence Diagram
4.2.4 Use Case 03E: Alert of High Level of Pollen in Area
Use case Id
UC03E
Title
Alert of high level of pollen in area
Involved building blocks Discovery Service, Processing System, Environmental System Involved applications
GAMBAS mobile application
Required data
Position of people, levels of pollen
Offered services
Alerts based on high concentrations on pollen
Involved partners
UDE, ETRA I+D, NUIG, OU
Table 14 – Alert of High Level of Pollen in Area Summary
The information retrieved thanks to the mechanisms described in the previous two use cases, can not only be used by a third party to build a pollution map of a city, but also directly by a GAMBAS application to subscribe to alerts on high concentration of pollen.
Gambas App
Discovery Service
Processing System
Environment System
Registre data service
Select alert pollution
Registre service
Stream query alert pollution
Capture context
Stream query location
update location
Query polution location
update polution warning
detect umbral polution
Figure 15 – Alert of High Level of Pollen in Area Sequence Diagram
In this use case, the GAMBAS application asks for the concentration of pollen related to its current position. The query could also be extended to the predicted position of the user, since this information is also available at the mobile application. A processing system is then in charge of obtaining the pollen concentration each time the GAMBAS apps update its position, and pushing an alert whenever the pollen pollution reaches a certain threshold – previously selected by the end user.
Of course, the user could consult at any time the pollution map of an area described in UC02E. However, the purpose of this use case is to automatically inform the user on the levels of pollen, based on the very same data that is used to build the maps, offering a customized service.
4.2.5 Use Case 03.1E: Alert of High Level of Pollen in Planned Bus Route
Use case Id
UC03.1E
Title
Alert of high level of pollen in planned bus route
Involved building blocks Discovery Service, Environmental System, Transport System Involved applications
GAMBAS mobile application
Required data
Desired destination, levels of pollen, routes
Offered services Alerts based on high concentrations on pollen on route Involved partners
UDE, ETRA I+D, NUIG, OU, ETRA
Table 15 – Alert of High Level of Pollen in Planned Bus Route Summary
As an extension to the previous use case, GAMBAS framework alerts the user about high levels of pollen in certain sections of its route. This is an additional piece if information to the adaptive trip planner functionality presented in the mobility scenario.
Gambas App
Discovery Service
Environment System
Transport System
Registre data service
Select alert pollution
Registre service
Registre service Discover services
Query route (OQP) Query polutions in points (OQP) Alerts
Figure 16 – Alert of High Level of Pollen in Planned Bus Route Sequence Diagram
This use case explores all the capabilities offered by the GAMBAS approach. Neither the Environmental nor the Transport System has all the information to respond to the user query “alert if pollen in route is high”. They cannot either provide individually a route considering the pollution as This use case explores all the capabilities offered by the GAMBAS approach. Neither the Environmental nor the Transport System has all the information to respond to the user query “alert if pollen in route is high”. They cannot either provide individually a route considering the pollution as
4.2.6 Use Case 04E: Urban Tolling Depending on CO2 Pollution
Use case Id
UC04E
Title
Urban tolling depending on CO2 pollution
Involved building blocks Discovery Service, Processing System, Environmental System, Tolling Layer
Involved applications
GAMBAS mobile application
Required data Desired destination, tolling information, CO2 levels Offered services
Adaptive trip plan based on pollution levels, notifications urban tolling prices depending on CO2 emissions.
Involved partners
UDE, ETRA I+D, NUIG, OU
Table 16 – Urban Tolling Depending on CO2 Pollution Summary
Nowadays urban tolling is mainly used to reduce pollution and traffic in the most congested areas of
a city. The policies behind it normally rely on statistical or real time information on levels of CO2 and the characteristics of the vehicles – e.g. type of engine, year of manufacturing, etc. With this information, authorities may decide the number and kind of vehicles allowed in a certain area on a certain period of time.
In this use case the objective is to provide the mechanisms to adapt the policies in place and modify the behavior of drivers by affecting the price to access a polluted area depending on the levels of CO2. Thus, the GAMBAS framework serves to calculate a variable toll for private vehicles accessing areas with high pollution levels.
Gambas App
Discovery Service
Processing System
Environment System
Tolling Layer
Registre data service
Discover services
Registre service Registre service
Query polution Areas Capture context
Calculate tolling
Query info city toll
Query Tolling Tax (OQP)
Figure 17 – Urban Tolling Depending on CO2 Pollution Sequence Diagram
The system could be as complex as required, considering not only the levels of CO2, but also other pieces of data that the users should have to share in order to circulate through certain CO2 saturated districts – e.g. type of vehicle, number of passengers, etc. The information could be provided through
a GAMBAS application, or also through other sensors embedded in the vehicle, similarly to the EFISAE component described for the public transport. This will allow the authorities to promote a GAMBAS application, or also through other sensors embedded in the vehicle, similarly to the EFISAE component described for the public transport. This will allow the authorities to promote
Moreover, the tolling could not only depend on the levels of CO2, but also on the noise levels – much more critical in certain areas.
In order to be able to implement this use case, a Smart City Tolling layer should be provided – out of the scope of the project. This layer could also be used by authorities to implement shadow toll policies based on number of vehicles in inter-urban roads.
4.2.7 Use Case 04.1E: Alert If Urban Tolling Higher than a Certain Price in Planned Route
Use case Id
UC04.1E
Title
Alert if urban tolling higher in a planned route
Involved building blocks Discovery Service, Processing System, Environmental System, Tolling Layer
Involved applications
GAMBAS mobile application
Required data Desired destination, tolling information, CO2 levels Offered services
Adaptive trip plan based on pollution levels, notifications urban tolling prices depending on CO2 emissions.
Involved partners
UDE, ETRA I+D, NUIG, OU
Table 17 – Alert If Urban Tolling Higher than a Certain Price in Planned Route Summary
As an extension on the previous presented use case, the user may prefer to program an alert whenever the fee to access a certain area with an urban tolling system reaches a certain price.
This functionality is actually the natural complement to the functionality presented at UC04E, where the objective was to grant the authorities with the mechanisms to establish new adaptive policies. If such policies were in place, drivers would require not only to access the current cost of the toll, but also to be notified about changing prices in real time. This would be especially critical if the authority adopted complex algorithms to establish the final price.
Gambas App
Discovery Service
Processing System
Environment System
Tolling Layer
Registre data service
Discover services
Registre service Registre service
Query polution Areas Calculate tolling
Query Tolling Area (OQP)
loop travel ( UC01M ) Detect near toll area
Query Tolling Tax (OQP)
Alert
Figure 18 – Alert If Urban Tolling Higher than a Certain Price in Planned Route Sequence Diagram
Both UC04E and UC04.1E could be combined with the following use case to promote the use of public transport and reduce the environmental footprint per passenger (UC06E).
4.2.8 Use Case 05E: Public Transport Incentives Depending on Pollution Levels
Use case Id
UC05E
Title Public Transport Incentives depending on Pollution levels Involved building blocks
Discovery Service, Processing System, Transport System Involved applications
GAMBAS mobile application, EMT Public transport Exploitation System Required data
Desired destination, CO2 levels, prices
Offered services Suggested public transport route with incentives in response to a high pollution level.
Involved partners
UDE, ETRA I+D, NUIG, OU, EMT
Table 18 – Public Transport Incentives Depending on Pollution Levels Summary
Complementing the policies at UC04E, this use case could be used by municipalities to incentive the use of public transport whenever a pollution crisis is detected – high levels of CO2 in an urban area.
The business case could rely in a sort of shadow tolling for citizens, where the municipality would cover the costs of the incentives, paying the transport operator for each of the citizens moving from private to public modes of transport.
From the point of view of feasibility, this is one of the most difficult use cases to be implemented, since it requires the active involvement of an authority willing to promote this shift in citizens’ mobility behavior. Nevertheless, shadow tolling is a concept extensively employed in transport, and the transferability of this approach to people could be studied.
In the context of GAMBAS, the interest is to explore the feasibility from a technical point of view, thanks to the tools and components provided within the project.
Gambas App
Discovery Service
Transport System
Environment System
PTES EMT
Registre data service
select info layers
Registre service
Discover services
Query pollution data Publish company info
Calculate promotion Stream Query Transport Notifications [CQP] Tranport Company Notifications
Figure 19 – Public Transport Incentives Depending on Pollution Levels Sequence Diagram
4.2.9 Use Case 06E: Environmental Footprint for Public Transport Passengers
Use case Id
UC06E
Title Environmental footprint for public transport passengers Involved building blocks
Discovery Service, Transport System
Involved applications
GAMBAS mobile application
Required data Desired destination, routes, number of passengers in bus, CO2 emissions from bus
Offered services Customized Environmental footprint based on real time data from bus Involved partners
UDE, ETRA I+D, NUIG, OU, EMT
Table 19 – Environmental Footprint for Public Transport Passengers Summary
Thanks to the already existing eco-driving systems in the public transport network operated by EMT – described in UC02E, it is possible to calculate the CO2 emissions per bus between two different points of a route.
In order to make use of this data and provide the CO2 emissions per passenger, it is necessary to establish the number of passenger in the bus at each time. This can be achieved through different mechanisms. In other mode of transports – such as subway – it is achieved through the use of specific access turnstiles; in GAMBAS it is achieved by the same mechanisms described in UC05x: the onboard control unit (BIT) is capable of detecting passengers getting on and off the bus by detecting the MAC addresses of their smartphones.
At the end of a stretch between two consecutive bus stops, the transport system can update the information on the number of passenger and the CO2 emissions in a specific stretch for a specific bus. These emissions will depend on the conditions of the bus – mainly the use of heat, ventilation and air condition systems, HVAC - the behavior of the driver, and the traffic conditions.
Figure 20 – Environmental Footprint for Public Transport Passengers Sequence Diagram
Once the CO2 emissions per passenger and stretch are available, the information can be used by the transport system to calculate the specific environmental footprint of a traveler. This can be later sent to the end-user.
The implementation of this use case opens the door to other functionalities described in this document, as UC04xE Urban tolling and UC05E Public transport incentives. Furthermore, it complements somehow the functionality addressed by UC5xM Number of passengers per bus.