A Household Solid Waste Sorting And Recognition Recycling System

Low recycling and low sorting rate are the long-term problems not only in Malaysia but all the developing country like Vietnam and Thailand. However, this project was focused on the recycling and sorting problem in Malaysia only. The proposed application is specially designed for Malaysian. With a population of 32 million, Malaysia generates more than 28000 metric tonnes of solid waste everyday. Surprisingly, only 10% of it are collected for recycling purpose. What is more, the single-stream recycling system practiced among Malaysia results in more contamination and low quality of recyclable solid waste. Hence, the proposed application is developed to stop these two problems. The objectives of this project are to identify the current limitation of the existing application of the recycling system, develop a mobile application that helps provide information regarding sorting recycled solid waste into categories based on image recognition using a neural network and evaluate the functionalities of the proposed system. After research done on three existing applications, it can be found that the existing applications will only focus more in sorting the household solid waste. However, for this proposed application, the Places API is implemented so that nearby recycling location are provided to the users and they can know where to send their recyclable waste. For those recyclable waste that cannot send by the user themselves, they can book a doorstep collection from the recycling center. Agile methodology consisting of requirements phase, design phase, develop phase, test phase, and deploy phase will be implemented for the development of the proposed application. Lastly, a User Acceptance Test were conducted in order to detect any defects of the proposed application. Current market in Malaysia still lack of this kind of recycling and sorting mobile application that helps push forward the milestones of recycling and sorting. That why I am here to contribute my effort to do so. The proposed application's expected outcome is to witness an increase in the number of persons participating in recycling activities. Perhaps these can reduce the household solid waste generated by Malaysian and indirectly contribute to a clean and safe environment. The second expected outcome is to public involved in the dual-stream recycling system and help collect more pure material and higher recycled waste recovery. Future work that needs to be done includes increasing dataset of machine learning training model of household solid waste from 30 to 100 so that diverse household solid waste can be scanned by the user. The second improvement can be let the user manual adjust the searching area (radius) of nearby recycling location

Processo de Integração e Entrega Contínua para Aplicações Baseadas em Análise de Dados

Processos de entrega de software tradicionais não são eficientes para uma empresa que produz software se manter competitiva. A crescente necessidade de entregar software em ciclos cada vez mais curtos fomentou o crescimento de abordagens e tecnologias que permitam automatizar este tipo de processos. No entanto, estas abordagens apresentam limitações quando a qualidade de entrega do software depende da qualidade dos dados que o mesmo produz. Com isso em mente, o principal objetivo desta dissertação consiste em adotar um mecanismo de entrega de software automático, eficaz, eficiente e fiável dentro da proGrow S.A. de forma a que o seu principal negócio, que é a geração de informação a partir de dados recolhidos, seja feito da forma mais eficiente e fiável possível. Após a análise detalhada do estado de arte atual, foi elaborada uma solução que implementa uma pipeline de implantação que incluí uma estratégia de testes que desafia o paradigma de testes tradicional, projetada para o contexto das soluções desenvolvidas. Deste modo, a solução é capaz de entregar software automaticamente, garantindo a sua qualidade através de uma estratégia de testes robusta, capaz de validar a qualidade da aplicação através dos seus dados. Assim, a solução desenvolvida é capaz de reduzir o tempo de desenvolvimento de uma nova versão, bem como garantir que o processo de escrutínio para deteção de erros nos dados gerados é feito de forma automática e repetível, com o objetivo de criar um padrão de qualidade nos dados gerados.Traditional software delivery processes are not efficient for a company that produces software to remain competitive. The growing need to deliver software in ever shorter cycles has fostered the growth of approaches and technologies that make it possible to automate this type of process. However, these approaches have limitations when the quality of software delivery depends on the quality of the data it produces. With this in mind, the main goal of this dissertation is to adopt an automatic, effective, efficient and reliable software delivery mechanism within proGrow S.A. so that its core business, which is generating information from collected data, is done in the most efficient and reliable way possible. After a detailed analysis of the current state of the art, a solution was devised that implements a deployment pipeline that includes a testing strategy that challenges the traditional testing paradigm, designed for the context of the solutions developed. In this way, the solution is able to deliver software automatically, guaranteeing its quality through a robust testing strategy, capable of validating the quality of the application through its data. Thus, the solution developed is able to reduce the development time of a new version, as well as ensuring that the scrutiny process for detecting errors in the data generated is done automatically and repeatably, with the aim of creating a quality standard in the data generated