The Backbone of Real-time Environmental Apps in Taiwan
Scenario & Goals
Due to the advancement of cloud computing and cloud storage tech in recent years, sharing and streaming massive data in real-time is not a dream but a reachable goal now. Therefore, many countries are developing web platforms that can supply insensitive monitoring data to citizens for building creative applications. Among all kinds of data collected by the government, the data of transportation and environment has gained wide popularity because the apps using such data can improve people’s daily lives directly.
For people living in Taiwan, the awareness of environmental protection is even higher since the natural resources become so vulnerable for such a small island on the Ring of Fire. However, in the past, the environmental monitoring data were collected by different government agencies and often failed to be organized well for further applications. To solve this issue, since 2013, Taiwan’s EPA (Environmental Protection Administration) has started a project called EnviroCloud, aiming to integrate all environmental data into the same cloud platform and making them more available for citizens and other government agencies.
As mentioned in the previous section, the goal of EnviroCloud is to establish an integrated platform supplying various kinds of environmental monitoring data to develop applications. To achieve this ambitious goal, there are several subsystems in the EnviroCloud, including a subsystem to accept data from different sources and then distribute them to another subsystem called CDX, a subsystem to store historical data called ERDB, a subsystem to provide real-time monitoring data for private organizations called OpenData.epa, and so on.
Among these subsystems, the most frequently used subsystem is OpenData.epa because it has four main features that can meet people’s need.
- First, its data comes from a single and reliable source- CDX, which secures the quality of data and avoids importing data repeatedly.
- Second, to help people create value-added applications, another main feature of OpenData.epa is providing real-time monitoring data readable by machines. That is, most of the data is provided in XML or JSON formats and will be updated automatically, which can be directly processed by computers. In this way, developers can create applications with ease by embedding the path in the program so that the real-time data will always be shown on the front end.
- The third is the feedback and response mechanism. The system administrator will check the data several times before its official release. After the data is published, the platform manager will keep adopting useful feedbacks from users to ensure the data will obtain great satisfaction from most people.
- Finally, the geospatial datasets are specially gathered and archived because they can be integrated with GIS software and mapped on mobile, desktop, or web applications instantly.
Fig. 1 Geospatial datasets are specially gathered and archived for people to utilize
Results & Benefits
Since OpenData.epa provides so much valuable data, many useful applications have been created thanks to this service. Some of them are really popular and widely-used in Taiwan.
- ASUS, the worldwide laptop manufacturing giant, has acquired the data from this platform to create its built-in weather app- ASUS Weather.
- Developed by EPA and Supergeo project team, Environmental Info Push App streams the data provided by OpenData.epa. It is now the most popular app on both Android and iOS that shows the latest environmental monitoring data in Taiwan. There are still dozens of other apps that have used this platform. Among all provided data, the most beloved ones are Air Quality Index, UV monitoring data, precipitation at ten-minute intervals, and air quality forecast.
- Now, this platform integrates more than a thousand datasets collected by over 20 government agencies and is supposed to reach over 600 registered user ends. In addition, the data on this platform is estimated to be downloaded and viewed for 71 million times and 2.6 million times respectively.