Smart Bitcoin Alert System

Abstract

Bitcoin, a decentralized digital currency, operates without the involvement of traditional financial institutions. Bitcoin transactions are conducted directly between parties, without the use of intermediaries, thanks to blockchain technology. Wallets, public keys, and private keys are necessary for the secure transactions of this cryptocurrency. Transaction can take place using Bitcoin simply going via centralized exchanges, in contrast with numerous other cryptocurrencies. This paper explores the unique features of Bitcoin and its advantages over other crypto assets. Notably, the decentralized and distributed ledger of blockchain technology ensures the secure storage of verified bitcoin transactions by network nodes. This distinguishes Bitcoin from assets that rely on centralized exchanges for verification. Recognizing the growing acceptance of Bitcoin in various transactions, including those conducted by small businesses, this research focuses on the need for accurate early prediction of Bitcoin prices. The study proposes leveraging machine learning algorithms, specifically Random Forest and Deep Learning (Long Short Term Memory), to predict the open and close values of Bitcoin. This predictive analysis aims to assist investors in making informed decisions and optimizing their Bitcoin investments. Accurate early forecast of Bitcoin prices is a need, as this research highlights, given the increasing use of Bitcoin in a variety of activities, including small company transactions. In order to forecast the open and closing prices of Bitcoin, the study suggests using machine learning techniques, notably Random Forest and Deep Learning (Long Short Term Memory). By using predictive analysis, investors may maximize their Bitcoin investments and make well-informed judgements. The study emphasizes the importance of accurate price predictions for Bitcoin investors and introduces machine learning algorithms as effective tools for achieving this goal. A comparative analysis of Random Forest and Long Short Term Memory algorithms will be conducted to evaluate their accuracy in predicting Bitcoin prices. The research aims to provide investors with valuable insights into optimizing their investment strategies based on reliable early predictions of Bitcoin values. This idea is reliable using Machine Learning which provides effective results. By Comparing the accuracy between two algorithms the prediction of bitcoin will be implemented. This can be done using Machine Learning Algorithm (Random Forest) and Deep Learning Algorithm (Long Short Term Memory). This prediction will help the bitcoin investors to identify the open and close value of the bitcoin so that the investors can invest their bitcoin in an efficient manner and get benefited.