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Digitalization of Hindu Temples in India in Google Cloud and SerpAPI Automation in Python

Received: 12 July 2022     Accepted: 8 August 2022     Published: 17 August 2022
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Abstract

The study on scraping the Google Search Engine via the SerpAPI and automatically generating a dataset of the temple name, location of the temple, temple description, the state of India, longitude and latitude coordinates, and distance from the major cities in India is demonstrated. The workload orchestration is controlled by Google Composer in Apache Airflow. Google Kubernetes Engine (GKE) categorizes applications into microservices under each container. The docker image is created in the GKE control plane, API scheduler segments the granular levels of microservices in the DevOps operation of GitHub, Jenkins. YAML provides the configuration of the pod, of GKE carrying multiple containers, of the main type of input for Kubernetes configurations. Python application creates the YAML for GKE configuration data to define the Kubernetes object and the business rule. The Google native artificial intelligence VertexAPI picks the keyword of the temple name and the location of every state in India. The SerpAPI application digitized the Hindu temples in India for the complete project life cycle for requirement gathering, design, development, and deployment in Google Cloud. The search parameters are designed for Google Search Engine for the collection of historians, and architectural details of the Hindu temples in India. The Google Search application uses the Google Compute Engine, Big Query, Google Kubernetes Engine, Cloud Composer, and big data services of Data Fusion, Dataproc, and Dataflow. The solution uses Google cloud services of Web Hosting, Load balancing, Google Storage, and the compute engine performance tuning in Big Query optimization. The Google search results are in JSON format of every state in temple details and a python application parses the facts on the Search API algorithm. The temple images are visualized in Python Application and integrated for the data visualization of Google inbuilt Google Studio.

Published in International Journal of Information and Communication Sciences (Volume 7, Issue 3)
DOI 10.11648/j.ijics.20220703.12
Page(s) 66-81
Creative Commons

This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.

Copyright

Copyright © The Author(s), 2022. Published by Science Publishing Group

Keywords

Google Cloud Big Query, Google Data Studio, Python Application Modernization, Data Analytics Engine, SerpAPI Scrape Algorithm, Hindu Temples India, Google Kubernetes Engine, Google Search Dataset

References
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Cite This Article
  • APA Style

    Ramamurthy Valavandan, Subramanian Jagathambal, Gothandapani Balakrishnan, Malarvizhi Balakrishnan, Valavandan Valvandan, et al. (2022). Digitalization of Hindu Temples in India in Google Cloud and SerpAPI Automation in Python. International Journal of Information and Communication Sciences, 7(3), 66-81. https://doi.org/10.11648/j.ijics.20220703.12

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    ACS Style

    Ramamurthy Valavandan; Subramanian Jagathambal; Gothandapani Balakrishnan; Malarvizhi Balakrishnan; Valavandan Valvandan, et al. Digitalization of Hindu Temples in India in Google Cloud and SerpAPI Automation in Python. Int. J. Inf. Commun. Sci. 2022, 7(3), 66-81. doi: 10.11648/j.ijics.20220703.12

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    AMA Style

    Ramamurthy Valavandan, Subramanian Jagathambal, Gothandapani Balakrishnan, Malarvizhi Balakrishnan, Valavandan Valvandan, et al. Digitalization of Hindu Temples in India in Google Cloud and SerpAPI Automation in Python. Int J Inf Commun Sci. 2022;7(3):66-81. doi: 10.11648/j.ijics.20220703.12

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  • @article{10.11648/j.ijics.20220703.12,
      author = {Ramamurthy Valavandan and Subramanian Jagathambal and Gothandapani Balakrishnan and Malarvizhi Balakrishnan and Valavandan Valvandan and Archana Gnanavel and Subramanian Kangalakshmi and Ramamurthy Savitha},
      title = {Digitalization of Hindu Temples in India in Google Cloud and SerpAPI Automation in Python},
      journal = {International Journal of Information and Communication Sciences},
      volume = {7},
      number = {3},
      pages = {66-81},
      doi = {10.11648/j.ijics.20220703.12},
      url = {https://doi.org/10.11648/j.ijics.20220703.12},
      eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ijics.20220703.12},
      abstract = {The study on scraping the Google Search Engine via the SerpAPI and automatically generating a dataset of the temple name, location of the temple, temple description, the state of India, longitude and latitude coordinates, and distance from the major cities in India is demonstrated. The workload orchestration is controlled by Google Composer in Apache Airflow. Google Kubernetes Engine (GKE) categorizes applications into microservices under each container. The docker image is created in the GKE control plane, API scheduler segments the granular levels of microservices in the DevOps operation of GitHub, Jenkins. YAML provides the configuration of the pod, of GKE carrying multiple containers, of the main type of input for Kubernetes configurations. Python application creates the YAML for GKE configuration data to define the Kubernetes object and the business rule. The Google native artificial intelligence VertexAPI picks the keyword of the temple name and the location of every state in India. The SerpAPI application digitized the Hindu temples in India for the complete project life cycle for requirement gathering, design, development, and deployment in Google Cloud. The search parameters are designed for Google Search Engine for the collection of historians, and architectural details of the Hindu temples in India. The Google Search application uses the Google Compute Engine, Big Query, Google Kubernetes Engine, Cloud Composer, and big data services of Data Fusion, Dataproc, and Dataflow. The solution uses Google cloud services of Web Hosting, Load balancing, Google Storage, and the compute engine performance tuning in Big Query optimization. The Google search results are in JSON format of every state in temple details and a python application parses the facts on the Search API algorithm. The temple images are visualized in Python Application and integrated for the data visualization of Google inbuilt Google Studio.},
     year = {2022}
    }
    

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  • TY  - JOUR
    T1  - Digitalization of Hindu Temples in India in Google Cloud and SerpAPI Automation in Python
    AU  - Ramamurthy Valavandan
    AU  - Subramanian Jagathambal
    AU  - Gothandapani Balakrishnan
    AU  - Malarvizhi Balakrishnan
    AU  - Valavandan Valvandan
    AU  - Archana Gnanavel
    AU  - Subramanian Kangalakshmi
    AU  - Ramamurthy Savitha
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    DO  - 10.11648/j.ijics.20220703.12
    T2  - International Journal of Information and Communication Sciences
    JF  - International Journal of Information and Communication Sciences
    JO  - International Journal of Information and Communication Sciences
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    EP  - 81
    PB  - Science Publishing Group
    SN  - 2575-1719
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    AB  - The study on scraping the Google Search Engine via the SerpAPI and automatically generating a dataset of the temple name, location of the temple, temple description, the state of India, longitude and latitude coordinates, and distance from the major cities in India is demonstrated. The workload orchestration is controlled by Google Composer in Apache Airflow. Google Kubernetes Engine (GKE) categorizes applications into microservices under each container. The docker image is created in the GKE control plane, API scheduler segments the granular levels of microservices in the DevOps operation of GitHub, Jenkins. YAML provides the configuration of the pod, of GKE carrying multiple containers, of the main type of input for Kubernetes configurations. Python application creates the YAML for GKE configuration data to define the Kubernetes object and the business rule. The Google native artificial intelligence VertexAPI picks the keyword of the temple name and the location of every state in India. The SerpAPI application digitized the Hindu temples in India for the complete project life cycle for requirement gathering, design, development, and deployment in Google Cloud. The search parameters are designed for Google Search Engine for the collection of historians, and architectural details of the Hindu temples in India. The Google Search application uses the Google Compute Engine, Big Query, Google Kubernetes Engine, Cloud Composer, and big data services of Data Fusion, Dataproc, and Dataflow. The solution uses Google cloud services of Web Hosting, Load balancing, Google Storage, and the compute engine performance tuning in Big Query optimization. The Google search results are in JSON format of every state in temple details and a python application parses the facts on the Search API algorithm. The temple images are visualized in Python Application and integrated for the data visualization of Google inbuilt Google Studio.
    VL  - 7
    IS  - 3
    ER  - 

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  • Nature Labs, Google Projects, Coimbatore, India

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