- freely available
Smart Cities 2019, 2(1), 46-65; https://doi.org/10.3390/smartcities2010004
- Traffic load: The monitoring of traffic conditions in order to verify and to monitor vehicle speeds is an important service in urban centers, but it is also a complex task. This is due, among other factors, to the presence of various traffic elements (pedestrians, motor vehicles, and non-motorized vehicles), often on a large scale. This problem encourages the development of mechanisms to estimate the traffic load and to predict it;
- Traffic planning: Efficient mobility planning is achieved when the traffic load is known, allowing modifications in the traffic flows and also advising the construction of new roads, bridges, and viaducts. For this, historical traffic information is highly required;
- Public data: The CitySpeed platform acquires data about vehicle speeds and stores such data in a public and open database, which can then be easily exploited by any other application. Such data can also be retrieved in a well-formatted standard (JSON);
- Historical data: All acquired data are available to be accessed, allowing historical processing and visualization of vehicle speeds. This may be highly desirable for better planning of traffic and general mobility in modern cities;
- Speed computing confidence: The speeds are sampled and stored based on global positioning service (GPS) reading, which is a cheap and acceptable mechanism for this purpose. Measurements through the OBD-II interface were also performed and the results were compared to the chosen method, validating it (discussed in Section 4);
- Data visualization: Although the platform is mostly aimed at providing public data, some reference visualization methods were also implemented, allowing different forms of graphical presentation of the data.
2. Related Works
3. The CitySpeed Platform
- The source code of all parts of the platform is public and can be freely used and/or altered. The code is available on the Github platform, and can be downloaded from “https://github.com/lablara/cityspeed.git”;
- The CitySpeed platform was developed to be ubiquitous, to consume low amounts of energy, and to require low storage space on smartphones;
- In order to reduce communication costs, all collected data are only transmitted to the proper server when a smartphone is connected to a Wi-Fi network. This standard behavior can be changed by the user, allowing smartphones to transmit data through 3G/4G connections;
- The platform was developed to be smoothly executed on Android and IOS smartphone systems; and
- Web-based graphical tools were developed, allowing different types of visualization of the retrieved data.
3.1. Logical Blocks
- GPS-based speed monitoring: Instantaneous speeds are continuously acquired and stored locally in a smartphone (CitySpeed_App);
- Speed data are transmitted and permanently stored in the system’s database: The designed app transmits the previously stored data to the configured server (CitySpeed_Server);
- Transmission confirmation: This allows a smartphone app to safely remove the temporarily stored data (CitySpeed_App);
- Data are transformed and stored in a second database: Speed data can now be publicly accessed (CitySpeed_Server);
- Data are retrieved to be processed and displayed: Different visualization pages are available, but any extensions can be developed (CitySpeed_Viewer).
- Timestamp: The time in which the speed sample was generated;
- Speed: Directly acquired from the GPS receiver. The API does not compute it, since it is provided by the GPS module on modern smartphones;
- Latitude: The latitude information provided by the GPS receiver and associated to the computed speed; and
- Longitude: The longitude information provided by the GPS receiver and associated to the computed speed.
- Time queries: A date range, or even a time frequency, may be specified, showing speed information for that time, every day in a period;
- Address queries: A country, city, and street may be used as search parameters, allowing different levels of specifications of the search set;
- Radius queries: A spot is selected on the displayed map and a radius may be defined in meters, retrieving data for the defined area.
3.2. Development Issues
3.3. Privacy and Security Concerns
4. Results and Experiments
4.1. Validation of Speed Computing
4.2. Monitoring in Urban Areas
5. Perspectives of the CitySpeed Platform for Smart Cities
5.1. Crowdsensing and People Engagement
5.2. Potential Applications
Conflicts of Interest
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|Hu et al. ||2013||Generic tasks||A generic task-centric platform with additional reliability guarantees.|
|Cardone et al. ||2016||Generic tasks||A platform for crowdsensing performed by students. It may define “tasks” for the users.|
|Dutta et al. ||2016||Air pollution||An additional device is attached to smartphones, which participates by providing information about air quality.|
|Zappatore et al. ||2016||Sound||Embedded microphones in smartphones are used to provide information about noises.|
|Wang et al. ||2016||Vehicular speeds||Acquires vehicular speeds and employs correlation methods to provide perceptions of average speeds over roads.|
|Silva et al. ||2019||Vehicular emissions||This crowdsensing platform acquires pollution data from OBD-II interfaces and distributes them through smartphones.|
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