Application Type: Native
Brief:The present research is conducted
in the city of Santo Domingo, Dominican Republic. The data collection will be
composed by two waves of GPS smartphone data.An app is designed to collect
mobility data. Via this app, the user movements are tracked over two weeks per
wave. A household survey will be conducted with the objective to: identify the
mobility patters, and invite the respondents to use the app (mapping).
Some Similar Apps/Websites: The app will be constructed over MEILI,
which is an open source app described in a subsection below. However, the APP
will have, in addition to MEILI, an user interface on the phone. The
application is expected to be able to:
The app will be able to carry out a
collection of mobility data with positioning coordinates (latitude-longitude)
taking into account the following:
Collection of GPS data
integrated in the mobile running in the background. The code of MEILI will be taken as a basis. A background data
collection system will be developed. The user can close the application, it
will be in the background with a notification in the status bar during the data
The app will detect the Origin
and destination as the start and end of the trips.
Link with maps openstreetmaps (or similar) obtaining
cross information from the transport network and development of activities (mapmatching).
Trip detection, destination/place
Following the MEILI app, this app will
detect places and activity destinations (POI), to assign a purpose as education
(school), work, shopping, doctor, etc.
Based on the MEILI mode detector, this app will be able
to distinguish public transport from private. For example: buses, public cars,
scooters, motorcycles, private vehicles, Metro, cable car, etc.
The app will detect at which
public transport stop the person and multimodal trips are located (see Figure 5).
Note: The detection of the metro, OMSA and
the cable car will be automatic whenever the user is walking and enters a
radius of 5 meters from the area of an official stop in the case of the OMSA
and station in the case of the metro and cable car.
The user's history will be taken into
account. When the same trip is undertaken (origin-destination), the user will
be notified that the previously used mode of transport has been assigned to the
trip. – verify if MEILI is already using
this machine learning part. –
The system will
be able to store routes in the phone and synchronize them when the phone
connects to a Wi-Fi network. Save the data collected directly in a local
database of the mobile device. When the device is connected to a Wi-Fi network,
the data stored locally will be synchronized by storing it in the database in
of a Web app is requested for the visualization of the data, dates and times in
which the data were taken. The web app design will be simple and functional, in
which it is possible for the user to:
Edit the routes created in the
mobile app and be able to segment them according to your mode of transport and
add your travel purpose separately. The user can segment the routes based on
the type of transport that was used in the different sections or cut segments
and join them with others regardless of the type of transport generating a new
Each segment must inform about
the mode of transport and its purpose of travel.
The segments will be divided by
user inactivity or change of transport mode.
Receive the data sent by the
APP mobile application and process it.
In addition to MEILI the app will have an
user interface accessible from the mobilephone. The app is expected to process
data on a server, view the data on the mobile phone, update the data in the
portal and store it in the database. See
Figures 3 and 4.
The app belongs to INTEC, will not be
shared, managed or sold by third parties.
Planning and payments
The developer will present a schedule and
milestones to connect with payments.
Two pilot tests will be carried out, to be
included in the planning, at the intermediate (50%) and final (100%) points of
the progress in the development of the application.
will work over MEILI and add the user interface available on the phone. The
following table shows a comparison of requirements and general information
about three reference apps. Basically, the app will have the following (five)
modules: trip collector, trip detection, mode detection, user interface and
online server. Features:
Social SignUp/SignIn (Facebook, Google, LinkedIn, Twitter)
Designs: UI Designs are ready (Some UI screens attached) / UI Designs are to be made.
APIs Status: APIs are already developed / Need to be developed
Backend Technology (APIs): APIs need to be developed in PHP/NodeJS
Timeline: 3-4 Months
Send a Proposal if you can do it and I will send a detailed Requirement Documents for further discussion if I shortlist your Proposal.