name of the application

How Long to Wait?


author(s), year

Zhou et al, 2012


short description of the application (one-two sentences)

A prototype of a bus arrival time predicitions system based on crowd-participatory sensing.


status of deployment (for example: real-life project, testing, demonstration, …)

one-time experiment

Target population

general, public transportation, users, car drivers, truck drivers, children, cyclists, …

public transportation

software type

open-source (in order to make unique campaigns) or proprietary software

proprietary software

transport mode

which modes of transport can be monitored (bicycle, public transportation, car, …)



who can launch a campaign

not defined

Sensing technologies

which type of sensors or methodes are used to obtain data

Microphone, accelerometer and mobile phone signal.

quantitative: what kind of data is measured

speed, distance, noise, location,…

Speed, location and vibrations ot the bus, noise from the card reader.

what type of qualitative data is gathered


what kind of data is calculated

CO², cost, health ; What is the basis of calculation (e.g. reference database, European guidelines for external costs, etc.)

Microphone detects audio indication signals of the busses card reader. The accelerometer is used to distinguish the travel pattern of buses to other transport means and the received celltower sequences are matched to the signature store in the database.

reporting method

which reporting method is used (for example: website or directly on the smartphone’s app, heat maps, dashboard, and/or reports)



method of reporting (visualisation) of the collected data (qualitative representation can be a red or a green light, a text explaining the progress, while quantitative representation consists of numbers or statistics



self-monitoring, gamification, rewards, social networks,…


applicability of results

are the results useable for policy-makers and how can they obtain this information?

The results can not be directly consulted because of the experimental phase of the project.


gaps and limitations of the campaign or application

The number of celltowers that a sharing user can capture on a bus influences the bus classification accuracy (referencing points). The number of sharing passengers affects the prediction accuracy in the system. The bus classification method needs a sufficiently long celltower sequences for accurate bus route classification, and consequently the arrival time at the first few bus stops would not be timely updated. efficiently and accurately classifying different bus routes sharing substantial portion of overlapped segments.


other important remarks for the review, links to other projects, …

A crowd-participated bus arrival time prediction system using commodity mobile phones.

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