Google Cloud Services for Collecting, Processing, Analyzing, and Visualizing the Types of COVID-19 Vaccines
Ramamurthy Valavandan,
Subhendu Ghosh,
Kumaraswamy Reddy,
Prasanth Parayatham,
Ubaiyadulla Sherif,
Vikram Sharma,
Pragathi Sri,
Vijayachandran Ramachandran,
Surasa Mukherjee,
Nitin Ambekar,
Dinesh Sai Teja Neeli,
Vijender Singh,
Santosh Baran,
Praveen Brian,
Hanumantha Raj,
Musheer Ahmed,
Saurabh Uniyal
Issue:
Volume 8, Issue 4, August 2022
Pages:
94-118
Received:
16 June 2022
Accepted:
11 July 2022
Published:
28 July 2022
DOI:
10.11648/j.ijdsa.20220804.11
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Views:
Abstract: This study analyzes the types of COVID-19 vaccines used in different countries in Google Cloud native services. Big Query, a Google Cloud data analytics product, is used for data analytics. The python application is developed for data visualization of types of COVID-19 vaccines, and the application deployed in Google Cloud handles the data collection methodology. Google Cloud composer establishes the connection to the World Health Organization portal. Apache Airflow directed acyclic graph (DAG) runs in a Cloud Composer environment and Google Data Studio for data visualization. Google Guild members fully support the Google cloud Nature Labs projects. The motivation behind this project is our recent work on creating the ecosystem in Google Cloud for customers. The discovery, identification of Google service, the workload migration is designed for Google Cloud. The python application parses the types of vaccines of COVID-19 data in JSON format. The big query, a serverless data analytics of Google cloud, performs the classes of vaccines used in different countries. The python application parses the JSON file format and generates the report of the types the COVID-19 vaccines. Python application performs the data visualization in Google cloud, and Google data studio completes the functional requirement of reporting layer. The approach to studying the types of vaccines used in different countries is unique. As always, the data clenching task is a tedious task. Thanks to the research sponsor, SerpAPI provides the Google search results of variance of COVID-19 vaccines and chemical composition of vaccines of companies. The developed solution and the work products are highly reusable, and customers benefit from the outcome of this research assignment in the Google cloud innovation project of Nature Labs. The Google cloud native offers the dynamics for the scientific community on the study of types of vaccines for vaccine manufacturing companies. We conclude that out of thirty vaccine manufacturing companies, the World Health Organization (WHO) disapproves of Wuhan CNBG.
Abstract: This study analyzes the types of COVID-19 vaccines used in different countries in Google Cloud native services. Big Query, a Google Cloud data analytics product, is used for data analytics. The python application is developed for data visualization of types of COVID-19 vaccines, and the application deployed in Google Cloud handles the data collecti...
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Mapping and Quantifying Green Area of Urban Villages from Google Satellite Images Using k-Means Clustering Algorithm
Veronica Sri Moertini,
Fritz Humphrey Silalahi
Issue:
Volume 8, Issue 4, August 2022
Pages:
119-130
Received:
29 July 2022
Accepted:
30 August 2022
Published:
14 September 2022
DOI:
10.11648/j.ijdsa.20220804.12
Downloads:
Views:
Abstract: It is well known that trees in cities are important as they produce oxygen, absorb rainwater, and provide shades. Due to urban development, the trees sufficiency in many cities is threatened. To maintain cities healthy environment, it is imperative that the local authorities monitor the trees adequacy from time to time and then act accordingly. For doing so, they need to be supported with quantitative data representing the adequacy of trees that can easily be accessed. In Indonesia, the lowest level of governmental administrative area is urban village. We view that if the data is provided for this level, it would be more effective as the head of the urban village can act or create necessary programs accordingly. Google updates regularly and provides satellite images that can be freely downloaded with many zoom-level. In urban areas, trees are visible with zoom-level of 16 and beyond. This research aims to develop a method for detecting/mapping trees green areas from urban village satellite images with the final result of green area (approximated in hectare unit). The method include village images preparation, detecting green areas based on image segmentation approach (using k-Means clustering algorithm), mapping and computing green area for each village. The case study is Bandung city, which is one of the most populated cities in Indonesia. The findings are potentially be used by the local authorities to evaluate the adequacy of trees in their territories.
Abstract: It is well known that trees in cities are important as they produce oxygen, absorb rainwater, and provide shades. Due to urban development, the trees sufficiency in many cities is threatened. To maintain cities healthy environment, it is imperative that the local authorities monitor the trees adequacy from time to time and then act accordingly. For...
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