Tata Consultancy Services Limited

Vishal Bajpai

Balamuralidhar Purushothaman

Jayavardhana Rama Gubbi Lakshminarasimha

Rishin Raj

Vishnu Hariharan Anand

Mahesh Rangarajan

Sreehari Kumar Bhogineni

Karthik Seemakurthy

Mayank Mishra

Shripad Salsingikar

Sunil D Joshi

Gopi Kandaswamy

Vineet Lall

Gourav Singh Jat

Kavita Sara Mathew

Dinesh Sasidharan Nair

Shashank Lipate

Pradeep Kumar Mishra

Gangadhar Shankarappa

Meghala Mani

Vishwa Chethan Dandenahalli Venkatappa

Jegan Mohan Ponraj

Srinivas Kotamraju

Vaibhav Vyawahare

Sunil Dattatraya Joshi

Mahesh Rangaraj

Rama Gubbi Lakshminarasimha Jayavardhana

Anand Vishnu Hariharan

Sasidharan Dinesh Nair

Current inspection processes employed for pipeline networks data acquisition aided with manually locating and recording defects/observations, thus leading labor intensive, prone to error and a time-consuming task thereby resulting in process inefficiencies. Embodiments of the present disclosure provide systems and methods for that leverage artificial intelligence/machine learning models and image processing techniques to automate log and data processing, reports and insights generation thereby reduce dependency on manual analysis, improve annual productivity of survey meterage and bring in process and cost efficiencies into overall asset health management for utilities, thereby enhancing accuracy in defect identification, analysis, classification thereof.

Identification of defect types in liquid pipelines for classification and computing severity thereof

This disclosure relates generally to systems and methods for data acquisition and asset inspection in presence of magnetic interference. Data acquisition and assets inspection systems in many infrastructures such as railway, power line, and bridges provide inaccurate results in presence of magnetic interference. The proposed system and method proposes UAV based navigation through a dynamic correction path to inspect one or more assets in one or more infrastructures. A plurality of sensors are integrated with the UAV to acquire images of the one or more assets in presence of magnetic field. The acquired images are further processed to segment and detect anomalies in one or more parts of the one or more assets. The detected anomalies are further classified as potential anomalies and non-potential anomalies. The proposed method provides accurate results with reduced processing time.

Systems and methods for data acquisition and asset inspection in presence of magnetic interference

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Bengaluru, India

Vishal Bajpai