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Using a Smart City IoT to Incentivise and Target Shifts in Mobility Behaviour--Is It a Piece of Pie?

Poslad S, Ma A, Wang Z, Mei H - Sensors (Basel) (2015)

Bottom Line: Whilst there is an increasing capability to instrument smart cities using fixed and mobile sensors to produce the big data to better understand and manage transportation use, there still exists a wide gap between the sustainability goals of smart cities, e.g., to promote less private car use at peak times, with respect to their ability to more dynamically support individualised shifts in multi-modal transportation use to help achieve such goals.We describe the development of the tripzoom system developed as part of the SUNSET-SUstainable social Network SErvices for Transport-project to research and develop a mobile and fixed traffic sensor system to help facilitate individual mobility shifts.This helps to promote mobility shifts towards achieving sustainability goals.

View Article: PubMed Central - PubMed

Affiliation: School of Electronic Engineering and Computer Science, Queen Mary University of London, Mile End Road, London E1 4NS, UK. stefan.poslad@qmul.ac.uk.

ABSTRACT
Whilst there is an increasing capability to instrument smart cities using fixed and mobile sensors to produce the big data to better understand and manage transportation use, there still exists a wide gap between the sustainability goals of smart cities, e.g., to promote less private car use at peak times, with respect to their ability to more dynamically support individualised shifts in multi-modal transportation use to help achieve such goals. We describe the development of the tripzoom system developed as part of the SUNSET-SUstainable social Network SErvices for Transport-project to research and develop a mobile and fixed traffic sensor system to help facilitate individual mobility shifts. Its main novelty was its ability to use mobile sensors to classify common multiple urban transportation modes, to generate information-rich individual and group mobility profiles and to couple this with the use of a targeted incentivised marketplace to gamify travel. This helps to promote mobility shifts towards achieving sustainability goals. This system was trialled in three European country cities operated as Living Labs over six months. Our main findings were that we were able to accomplish a level of behavioural shifts in travel behaviour. Hence, we have provided a proof-of-concept system that uses positive incentives to change individual travel behaviour.

No MeSH data available.


Structure of a “Target and Challenge” Incentive.
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sensors-15-13069-f005: Structure of a “Target and Challenge” Incentive.

Mentions: To manage incentives, the CD (City Dashboard) retrieves and sends incentive data from and to the IMP. LLc (Living Lab [human] controller) can register, retrieve, and modify incentives in IMP database. In addition, the CD supports LLc monitoring and incentive issuing to users, for example how many users received a new incentive notification. In total, there are two main tasks on incentive management now in the CD: registration and modification of incentives; monitoring incentives. The IMP currently implements “Target and Challenge” incentives. These incentives are manually registered by a LLc through the CD. The structure of an incentive is displayed in Figure 5 below.


Using a Smart City IoT to Incentivise and Target Shifts in Mobility Behaviour--Is It a Piece of Pie?

Poslad S, Ma A, Wang Z, Mei H - Sensors (Basel) (2015)

Structure of a “Target and Challenge” Incentive.
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4507639&req=5

sensors-15-13069-f005: Structure of a “Target and Challenge” Incentive.
Mentions: To manage incentives, the CD (City Dashboard) retrieves and sends incentive data from and to the IMP. LLc (Living Lab [human] controller) can register, retrieve, and modify incentives in IMP database. In addition, the CD supports LLc monitoring and incentive issuing to users, for example how many users received a new incentive notification. In total, there are two main tasks on incentive management now in the CD: registration and modification of incentives; monitoring incentives. The IMP currently implements “Target and Challenge” incentives. These incentives are manually registered by a LLc through the CD. The structure of an incentive is displayed in Figure 5 below.

Bottom Line: Whilst there is an increasing capability to instrument smart cities using fixed and mobile sensors to produce the big data to better understand and manage transportation use, there still exists a wide gap between the sustainability goals of smart cities, e.g., to promote less private car use at peak times, with respect to their ability to more dynamically support individualised shifts in multi-modal transportation use to help achieve such goals.We describe the development of the tripzoom system developed as part of the SUNSET-SUstainable social Network SErvices for Transport-project to research and develop a mobile and fixed traffic sensor system to help facilitate individual mobility shifts.This helps to promote mobility shifts towards achieving sustainability goals.

View Article: PubMed Central - PubMed

Affiliation: School of Electronic Engineering and Computer Science, Queen Mary University of London, Mile End Road, London E1 4NS, UK. stefan.poslad@qmul.ac.uk.

ABSTRACT
Whilst there is an increasing capability to instrument smart cities using fixed and mobile sensors to produce the big data to better understand and manage transportation use, there still exists a wide gap between the sustainability goals of smart cities, e.g., to promote less private car use at peak times, with respect to their ability to more dynamically support individualised shifts in multi-modal transportation use to help achieve such goals. We describe the development of the tripzoom system developed as part of the SUNSET-SUstainable social Network SErvices for Transport-project to research and develop a mobile and fixed traffic sensor system to help facilitate individual mobility shifts. Its main novelty was its ability to use mobile sensors to classify common multiple urban transportation modes, to generate information-rich individual and group mobility profiles and to couple this with the use of a targeted incentivised marketplace to gamify travel. This helps to promote mobility shifts towards achieving sustainability goals. This system was trialled in three European country cities operated as Living Labs over six months. Our main findings were that we were able to accomplish a level of behavioural shifts in travel behaviour. Hence, we have provided a proof-of-concept system that uses positive incentives to change individual travel behaviour.

No MeSH data available.