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Predicting the Weather: Forecasting

Paper type: Essay
Pages: 6 (1431 words)
Categories: Climate, Data, Data Mining, Environment, Technology, Weather
Downloads: 25
Views: 2

Weather is the state of the atmosphere at a particular time and place with regard to temperature, moisture, air pressure, precipitation, etc. Bio organisms need to adapt with the changing atmospheric conditions. It is therefore important to know the atmospheric condition for different applications. The interest is to design of Arduino with sensors that can provide information of weather from anywhere without using Network. Here a hardware model has been designed and implemented. It is difficult to get accurate weather for a particular location.

With the advancement of technology, especially the embedded systems and the problem of large setup area and cost has been reduced signi?cantly. It is possible to provide an instant weather report with some different altitudes as well as for different time instant. In this project motivate to read temperature and humidity from DHT11 using Blynk and accelerometer, its work for measure the acceleration by measuring the change in capacitance.

The NodeMCU collects the temperature and humidity from the DHT11 sensor and sends it to the Blynk app every second. Arduino IDE, Blynk app before we dive into the code, let setup the Blynk app to receive the data from NodeMCU. The code connects the ESP8266 to the local WIFI network, reads the current time from the nearest device.

Introduction

The weather is a natural phenomenon always changes with the change of different atmospheric parameters. Still, the average or mean condition can be predicted which ultimately gives the climate of a geographical area for long time consideration. The most important parameters that affect the atmospheric conditions are air pressure, temperature, and humidity. All these parameters are subject to change with the change of altitude, day length (intensity of sunlight changes), environmental components (tropical zone, or temperate zone etc.), sun angle at a particular spot, etc.

In the modern system of weather forecasting, the environmental data are sent to a computer-based system through ACCELEROMETER Micro-Electro-Mechanical Sensors (MEMS). Multiple parameters are multiplexed and finally proceeding through a single channel to the computer to show the data by using with BYLNK which communicates through wireless data transmission system and displayed. Not very original but I decided to also build a weather station. But this version with a NodeMCU (8266) controller display to BLYNK and DHT11 sense the ratio of moisture and air to the highest amount of moisture at a particular air temperature to read using with ESP2866 and Arduino.

This paper mainly combines two-study fields based control systems and data acquisition technique, to create a database system depending on the employed attributes to generate the presented data. The main attributes have been chosen based on the sensors used to build the system in order to create an effective weather station project. The proposed sensors used to measure and store Temperature, Humidity, and Wind speed data. The acquired data can be displayed in two ways identified as direct and indirect due to periodic data read and storing the data as a real database system respectively. Real database creation technology is considered the main challenge of this work, which gives an opportunity to mine the data, recorded in the past. Furthermore, the entire system supervises and governs locations locally based on the periodic change that occurs in the climate conditions, in order to keep the proposed locations in desired weather situations. Finally, the light-sensing module is included with the module to provide weather station system by the information regarding day/night times based light intensity

Weather forecasting using Arduino based cube-sat

Weather is the state of the atmosphere at a particular time and place with regard to temperature, moisture, air pressure, precipitation, etc. Bio organisms need to adapt with the changing atmospheric conditions. It is therefore important to know the atmospheric condition for different applications. The interest is to design an autonomous small cube satellite that can provide information of weather from anywhere without using Network. Here a hardware model has been designed and implemented. It is possible to provide instant weather report which can be used to compare the data of a place with some different altitude as well as for different time instant. In meteorology, the main objective is to know accurate weather conditions with less human efforts, reliable and efficient data. As the weather varies from place to place and with the altitude, it is dif?cult to get accurate weather for a particular location. With the advancement of technology, specially embedded system & data acquisition systems, the problem of large set up area and cost has been reduced signi?cantly. Cube’Sat can be set up at home as well as in the atmosphere or in space which can provide accurate weather reports.

The weather forecast using data mining research based on cloud computing

Weather Prediction is the application of science and technology to predict atmospheric conditions ahead of time for a particular region. Prediction is one of the basic goals of Data Mining. Data Mining is to dig out knowledge and rules, which are hidden and unknown. User may be interested in or has potential value for decision-making from the large amounts of data. Such potential knowledge and rules can reveal the laws between the data. There are many kinds of technical methods of data mining, which mainly include: association rule mining algorithm, decision tree classification algorithm, clustering algorithm and time-series mining algorithm, etc. [1]. How to store, manage and use these massive meteorological data, discover and understand the law and knowledge of the data, to contribute to weather forecasting completely and effectively has attracted more and more Data Mining researcher’s attention[2]. This article constructs the Weather Forecasting platform, using data mining for meteorological forecast and the forecast results are analyzed.

Analysis of the weather forecasting and techniques

Weather Forecasting is a scientific estimation of forecasting the weather. Weather is observing the state of the atmosphere at the given period of time. To predict the weather is one of the most challenging tasks for all the researchers and scientists. Parameters that are considered for predicting weather are temperature, rainfall, humidity, and wind. The prediction is made based on the past values. The future values are estimated based on the past meteorological record. Hence it is termed as a numerical based model. Weather plays a major role in Agriculture and the industries. Bringing out the Accuracy in the weather prediction is still under research. In this paper, we focus on various techniques that are used for weather prediction. Nearly about 10 papers are compared with their problem, techniques, and tools that are used in the paper with its own advantage and disadvantage. Several approaches are used in but the artificial neural network and the concept of fuzzy logic provide the best solution and prediction comparatively.

Methodology

It is difficult to get accurate weather for a particular location. With the advancement of technology, especially the embedded systems and the problem of large setup area and cost has been reduced signi?cantly. It is possible to provide an instant weather report with some different altitudes as well as for different time instant. In this project motivate to read temperature and humidity from dht11 using Blynk and accelerometer, its work to measure the acceleration by measuring the change in capacitance.

References

  • M. Zhang, Application of Data Mining Technology in Digital Library, Journal of Computers, vol. 6, no. 4, (2011) April, pp. 761-768.
  • Z. Danping and D. Jin, The Data Mining of the Human Resources Data Warehouse in University-Based on Association Rule”, Journal of Computers, vol. 6, no. 1, (2011) January, pp. 139-146.
  • Introduction to Data Mining and Knowledge Discovery, Third Edition, Two Crowds Corporation, accessed on 12 April 2009.
  • L. M. Saini and M. K. Soni, Artificial neural network-based peak load forecasting using conjugate gradient methods, IEEE Transactions on Power Systems, vol. 12, no. 3, pp. 907 912, . 2002.
  • S. Fan, C. X. Mao, and L. N. Chen, Peak load forecasting using the self-organizing map, in Advances in Neural Network-ISNN 2005. New York: Springer-Verlag, 2005, pt. III, pp. 640- 649.
  • Kourentzes, N., “Intermittent demand forecasts with neural networks, International Journal of Production Economics, Volume 143, Number 1, pages 198-206, 2013.
  • Elia G. P., 2009, “A Decision Tree for Weather Prediction”, Universitatea Petrol-Gaze din Ploiesti, Bd. Bucuresti 39, Ploiesti, Catedra de Informatic?, Vol. LXI, No. 1.
  • A. R. Finamore; V. Calderaro; V. Galdi; A. Piccolo; G. Conio; S. Grasso, A day-ahead wind speed forecasting using data-mining model- a feed-forward NN algorithm”, IEEE International Conference on Renewable Energy Research and Applications, 2015, pp. 1230-1235.
  • E. Erdem, J. Shi, “ARMA based approaches for forecasting the tuple of wind speed and direction”, Applied Energy 88, ELSEVIER, 2011, pp. 1405-1414.

Cite this essay

Predicting the Weather: Forecasting. (2019, Dec 02). Retrieved from https://studymoose.com/predicting-the-weather-forecasting-essay

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