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Main.TrafficOptimisationr1.7 - 22 May 2020 - 21:12 - GregorioIvanoff

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Traffic optimisation scenario


Português - It is a normal weekday morning. Carmen wakes and plans her travel for the day. She wants to leave for work in half an hour and asks AmI, by means of a voice command, to find a vehicle to share with somebody on her route to work. AmI starts searching the trip database and, after checking the willingness of the driver, finds someone that will pass by in 40 minutes. The in-vehicle biosensor has recognised that this driver is a non-smoker – one of Carmen requirements for trip sharing. From that moment on, Carmen and her driver are in permanent contact if wanted (e.g. to allow the driver to alert Carmen if he/she will be late). Both wear their personal area networks (PAN) allowing seamless and intuitive contacts.

While taking her breakfast coffee Carmen lists her shopping since she will have guests for dinner tonight. She would like also to cook a cake and the e-fridge flashes the recipe. It highlights the ingredients that are missing milk and eggs. She completes the shopping on the e-fridge screen and asks for it to be delivered to the closest distribution point in her neighbourhood. This can be a shop, the postal office or a franchised nodal point for the neighbourhood where Carmen lives. All goods are smart tagged, so that Carmen can check the progress of her virtual shopping expedition, from any enabled device at home, the office or from a kiosk in the street. She can be informed during the day on her shopping, agree with what has been found, ask for alternatives, and find out where they are and when they will be delivered.

Forty minutes later Carmen goes downstairs onto the street, as her driver arrives. When Carmen gets into the car, the VAN system (Vehicle Area Network) registers her and by doing that she sanctions the payment systems to start counting. A micro-payment system will automatically transfer the amount into the e-purse of the driver when she gets out of the car.

In the car, the dynamic route guidance system warns the driver of long traffic jams up ahead due to an accident. The system dynamically calculates alternatives together with trip times. One suggestion is to leave the car at a nearby ‘park and ride’ metro stop. Carmen and her driver park the car and continue the journey by metro. On leaving the car, Carmen’s payment is deducted according to duration and distance.

Out of the metro station and whilst walking a few minutes to her job, Carmen is alerted by her PAN that a Chardonnay wine that she has previously identified as a preferred choice is on promotion. She adds it to her shopping order and also sets up her homeward journey with her wearable. Carmen arrives at her job on time.

On the way home the shared car system senses a bike on a dedicated lane approaching an intersection on their route. The driver is alerted and the system anyway gives preference to bikes, so a potential accident is avoided. A persistent high-pressure belt above the city for the last ten days has given fine weather but rising atmospheric pollutants. It is rush hour and the traffic density has caused pollution levels to rise above a control threshold. The city-wide engine control systems automatically lower the maximum speeds (for all motorised vehicles) and when the car enters a specific urban ring toll will be deducted via the Automatic Debiting System (ADS).

Carmen arrives at the local distribution node (actually her neighbourhood corner shop) where she picks up her goods. The shop has already closed but the goods await Carmen in a smart delivery box. By getting them out, the system registers payment, and deletes the items from her shopping list. The list is complete. At home, her smart fridge screen will be blank.

Coming home, AmI welcomes Carmen and suggests to telework the next day: a big demonstration is announced downtown.

ISTAG. Scenarios for Ambient Intelligence in 2010. EC - Community Research - IST 2001. Available from < >. access on 5 December 2019.

Hospitality / Hospitalidade

This table shows the four areas of ilanet virtual infrastructure and its correspondence to ambient intelligence scenarios. / Esta tabela mostra as quatro áreas da infraestrutura virtual da ilanet e sua correspondência com os cenários de inteligência do ambiente.

1: Fiorella: personal ambient communicator / comunicador ambiente pessoal Efficiency / Eficiência (Express) 3: Carmen: traffic optimisation / otimização de tráfego
Personality / Individualidade (Persona)   Community / Comunidade (Ilanet)
2: Federico: connecting people and expressing identities / conectando pessoas e expressando identidades Sociability / Sociabilidade (Ágora) 4: Annette and Solomon / Salomão: social learning by connecting people and creating a community memory / aprendizagem social conectando pessoas e criando uma memória comunitária

-- GregorioIvanoff - 06 Dec 2019
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