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An Air Pollutant Real-time and Forecast Data Curve Interaction Method Used in Mobile

IP.com Disclosure Number: IPCOM000244209D
Publication Date: 2015-Nov-24
Document File: 5 page(s) / 290K

Publishing Venue

The IP.com Prior Art Database

Abstract

This disclosure discloses an air pollutant real-time and forecast data curve interaction method based on the needing in the air pollutant area while lots of data are used to shown air quality information, and users want to do some actions in curves in order to find useful info to make their decision. Considering lots of data showing in the mobile would not make the data information show clearly, a data extraction model is designed with mobile terminal resolution value and the curve control size value as the input, and the air pollutant real-time curve and forecast curve data as the output. While lots of the forecast curves are shown in this curve control and make these curves could not be used clearly, a drag function and drag out of the original curve function is provided in this curve control to let any of the curve can be moved into any place in this curve control, and also zoom in and zoom out function are also useful in this curve. Based on these functions provided by this curve control, any curve or any section of one curve can be drag to be new curve which will help users make their decision exactly.

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An Air Pollutant Real

An Air Pollutant Real- --time and Forecast Data Curve Interaction Method Used in Mobile

time and Forecast Data Curve Interaction Method Used in Mobile

Background

Air pollutant is very useful to show the environmental merits as more and more real-time data and forecast are get from outer or inner.

   And in order to see a long time range data in one curve control, there are lots of data number, so it is very small to plot the curve and also it will need lots of internet resource to get data from the backend data service.

   Many user also want to do some interaction with thecurve control to show the data difference between the real-time data and forecast data in the mobile terminal.

So it is very convenient if there is a good curve control which can make all the requirements become reality.

Current Solution and Problem

A curve control while whatever number of data are put into it, it just plot them.

   When user does the interaction action, many of the data need to take much time and resource to get these data from the backend data service.

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Problem

It is very slow to plot lots of data in on curve control.

It is very slow to get lots of data from the backend data service.

It is very vague when lots of real-time data and forecast data are plotted at one curve control. And when lots of curves shown in a curve control, lines info can not be understood clearly.

Our Idea

   The air pollutant real-time and forecast data are produced each day with one point per hour, so each day, there will be 24 points, and 24*30 points each month, and 24*30*12 points each year. When lots of data need to be shown in the mobile curve control, lots of data could not be shown very well. And as lots of data shown in one position of the x axis, we could not find what the difference between the real-time data and forecast data.

Input:

So in this curve interaction, all the actions are collected e.g drag, zoom in , zoom out and the speed during the three actions. Real-time data and forecast data stored in database or file.

The mobile terminal resolution value and the curve control size value.

Output:

Air pollutant real-time data curve and forecast data cure.

Drag the curve to anywhere in the curve control.

Drag out random length of the curve from the primary curve.

Process of our idea

The process can be disclosed as:

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1. Get the mobile terminal resolution value and the curve control size, and we can assume the resolution value in the control size as cx, cy, where cx is the resolution value in the horizontal direction and cy is the resolution value in the vertical direction.

2. Initially, obtain the current date and time of the mobile terminal, and obtain the corresponding air pollutant real-time and forecast data value.

3. Obtain the interaction during the curve c...