Ecosystem evolution analysis and trend prediction of projects in Android application framework

2020 ◽  
Author(s):  
Zhehao Fan ◽  
Zhiyong Feng ◽  
Xiao Xue ◽  
Shizhan Chen ◽  
Hongyue Wu
Keyword(s):  
Application Framework ◽  
Android Application ◽  
Trend Prediction ◽  
Evolution Analysis ◽  
Ecosystem Evolution

scholarly journals Spatiotemporal evolution analysis of NO2 column density before and after COVID-19 pandemic in Henan province based on SI-APSTE model

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Yang Liu ◽  
Jinhuan Zhao ◽  
Kunlin Song ◽  
Cheng Cheng ◽  
Shenshen Li ◽  
...  
Keyword(s):  
Air Pollution ◽  
Swarm Intelligence ◽  
Urban Areas ◽  
Pollution Source ◽  
Henan Province ◽  
Spatiotemporal Evolution ◽  
Trend Prediction ◽  
Vertical Column ◽  
Evolution Analysis ◽  
Before And After

AbstractAir pollution is the result of comprehensive evolution of a dynamic and complex system composed of emission sources, topography, meteorology and other environmental factors. The establishment of spatiotemporal evolution model is of great significance for the study of air pollution mechanism, trend prediction, identification of pollution sources and pollution control. In this paper, the air pollution system is described based on cellular automata and restricted agents, and a Swarm Intelligence based Air Pollution SpatioTemporal Evolution (SI-APSTE) model is constructed. Then the spatiotemporal evolution analysis method of air pollution is studied. Taking Henan Province before and after COVID-19 pandemic as an example, the NO2 products of TROPOMI and OMI were analysed based on SI-APSTE model. The tropospheric NO2 Vertical Column Densities (VCDs) distribution characteristics of spatiotemporal variation of Henan province before COVID-19 pandemic were studied. Then the tropospheric NO2 VCDs of TROPOMI was used to study the pandemic period, month-on-month and year-on-year in 18 urban areas of Henan Province. The results show that SI-APSTE model can effectively analyse the spatiotemporal evolution of air pollution by using environmental big data and swarm intelligence, and also can establish a theoretical basis for pollution source identification and trend prediction.

Android Application Based Real Time Home Automation

2011 ◽  
Vol 4 (7) ◽  
pp. 188-190 ◽  
Author(s):  
Kallakunta. Ravi Kumar ◽  
◽  
Shaik Akbar
Keyword(s):  
Real Time ◽  
Home Automation ◽  
Android Application

Myteam, an Android Application for Team Management

2012 ◽  
Vol 2 (3) ◽  
pp. 140-142
Author(s):  
Aabid A.S Mulani ◽  
◽  
Sagar A Patil ◽  
Yogesh R Khedkar
Keyword(s):  
Team Management ◽  
Android Application

Remote Heart Beat Monitoring System

2019 ◽  
Vol 7 (1) ◽  
pp. 5-10
Author(s):  
Saman Shahid ◽  
Saima Zafar ◽  
Mansoor Imam ◽  
Muhammad Usman Chishtee ◽  
Haris Ehsan
Keyword(s):  
Heart Diseases ◽  
Cost Effective ◽  
Heart Beat ◽  
The Internet ◽  
Android Application ◽  
Development Environment ◽  
Future Assessment ◽  
Pulse Sensor ◽  
Hospital Visits ◽  
Monitoring Module

There is an increased prevalence of heart diseases in developing countries and continuous monitoring of heart beats is very much important to reduce hospital visits, health costs and complications. The Internet of Things (IoT) equipped with microcontrollers and sensors can give an easy and cost-effective remote health monitoring. We developed a Heart Beat monitoring module based on an android application. The software involved was the Android Application developed using Android Studio, which is the Integrated Development Environment (IDE). This app retrieved the data from the open IoT platform thingspeak.com. A highly sensitive Pulse Sensor was used to measure the heartbeat of the patient automatically. An Arduino Uno microcontroller interfaced with a Wi-Fi module ESP8266 used to transmit pulse reading over the internet using Wi-Fi. The heartbeat was displayed on the LCD of the patient in run-time. The heartbeat in beats per minute (BPM) was plotted against time (minutes). A mounted pulse sensor to the patient had monitored the heartbeat and transmitted it in the form of voltage signal to the microcontroller, which converted it back into a mathematical value. The Arduino transmitted the data onto the thingspeak.com portal, where it was plotted on a graph and the values were stored for future assessment. The user of the app was given a things peak API and the channel number as an access code, through which physician or nurse can accessed the patient’s data. IoT based heartbeat module as an android application can provide a convenient, cost effective and continuous remote measurements for heart patients to help physicians and nurses update. This app can reduce the burden of hospital visits or admissions for elderly patients.

SMS Encryption on Android Application

2019 ◽  
Vol 7 (3) ◽  
pp. 528-533
Author(s):  
Shaik Quadar Janbee ◽  
Reddem Mouneeswari ◽  
Viswanadhapalli Bhanuja ◽  
Atmakuri Prashant
Keyword(s):  
Android Application
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