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Presented at the Panel Discussion on "Future of Big Data Analytics" at the AI & Big Data Analytics Conclave at Fore School of Management.
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Data Quality, Security and Usability are perpetual issues.
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We’ll show you how.
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Importance of data acquisition quality for artificial intelligence
1. Importance of Data Acquisition Quality for
Artificial Intelligence
Presentenced By:
Abhilash Saini
Geophysicist
TojoVikas International Pvt. Ltd.
2. Contents
• What is AI and how it works ?
• Need of AI in Geophysics (GPR Particularly)
• Need of Perfect Data Acquisition
• What is already done ?
• Conclusion
• References
3. What is AI ?
Artificial intelligence (AI) is the simulation of human intelligence processes by
machines, especially computer systems. These processes include learning (the
acquisition of information and rules for using the information), reasoning (using rules
to reach approximate or definite conclusions) and self-correction. Particular
applications of AI include expert systems, speech recognition and machine vision.
Source: https://searchenterpriseai.techtarget.com/definition/AI-Artificial-Intelligence
4. How it works ?
Source: https://www.kdnuggets.com/2019/03/work-data-science-ai-big-data.html
5. Need of AI in Geophysics (GPR Particularly)
• It is a Time Saver and accuracy is being
improved
• Solutions for Big Data Problems
• Money Making Machine
• Necessary to be in competition
• Opens new gates to setting allies in
International markets.
6. Need of Perfect Data Acquisition
• There are two things needed for AI
• The more accurate the training data the more
powerful the tool.
AI
Code
Training
Data
7. Need of Perfect Data Acquisition
• Training Data must be perfectly defined:
Training Data
Pipes
Wires
Septic
Tanks
Rebar
Further
Classifications
8. Need of Perfect Data Acquisition
• If you miss the details and insert the wrong data flagged as pipe which is not, then
code will be weak AI.
• If you take care of the training data set carefully and have its domain set to big
data set. AI will be Strong AI.
9. What is already done ?
Artificial Neural Networks and Machine Learning techniques applied to
Ground Penetrating Radar: A review
Author : Xisto L. Travassos et al. 2018.
DOI: https://doi.org/10.1016/j.aci.2018.10.001
They have 61 reviewed research papers including Basics and different AI
algorithms as references.
An Improved Convolutional Neural Network System for Automatically
Detecting Rebar in GPR Data
Author : Zhongming Xiang et. At. 2019.
They have established a system for detecting rebar in GPR data.
11. What is already done ?
MALA AI news and Press Release : https://www.guidelinegeo.com/news/mala-ai-worlds-first-for-interpretation-of-gpr-data/
MALA AI Presentation: https://www.youtube.com/watch?v=CFxahL8AIJI&feature=youtu.be
12. Conclusion
To achieve better solutions for the clients we need fast and more accurate approach, And that
includes AI, but without quality data AI will not work better it will become full of ambiguities.
We have to consider for the following things:
• GPR must be properly shielded, no source of coherent noise be there to reduce the quality of
raw data.
• GPR must be slowed down on rough patches of ground.
• Any Mobile, Radio or any electronic equipment must not be near during the acquisition.
• Even Big Buildings, Electric Poles etc. also creates noise so Survey Design must be done
considering these things.
• Where traffic must be preplanned so that team can cover such sites when there is less traffic
or no traffic at all. Traffic forecast can help in that using Google Maps or local People.
• Any other suggestions are also welcome to add on…
13. References
• https://searchenterpriseai.techtarget.com/definition/AI-Artificial-Intelligence
• https://www.guidelinegeo.com/news/mala-ai-worlds-first-for-interpretation-of-
gpr-data
• https://www.kdnuggets.com/2019/03/work-data-science-ai-big-data.html
• https://www.youtube.com/watch?v=CFxahL8AIJI&feature=youtu.be
• Ishitsuka et. al. 2018. Object Detection in Ground-Penetrating Radar Images Using
a Deep Convolutional Neural Network and Image Set Preparation by Migration.
International Journal of Geophysics. DOI: https://doi.org/10.1155/2018/9365184
• Pham et. al. 2018. BURIEDOBJECTDETECTIONFROMB-
SCANGROUNDPENETRATINGRADARDATA USINGFASTER-RCNN. DOI:
arXiv:1803.08414v1
• Xisto L. Travassos et al. 2018. Artificial Neural Networks and Machine Learning
techniques applied to Ground Penetrating Radar: A review. Applied Computing and
Informatics.DOI:https://doi.org/10.1016/j.aci.2018.10.001
• Zhongming Xiang et. At. 2019. An Improved Convolutional Neural Network System
for Automatically Detecting Rebar in GPR Data.
Editor's Notes
MALA AI news and Press Release : https://www.guidelinegeo.com/news/mala-ai-worlds-first-for-interpretation-of-gpr-data/
MALA AI Presentation: https://www.youtube.com/watch?v=CFxahL8AIJI&feature=youtu.be
