Inventor : Maheep Purohit
FIELD OF THE INVENTION
This invention pertains to the critical field of infrastructure monitoring, specifically
addressing the need for real-time detection, prediction, and proactive management of
integrity issues within vital pipeline networks, whether situated underground or
aboveground. These pipelines form essential conduits in sectors including oil and gas
transmission, water distribution, and chemical transport. At its core, this invention aims to
improve the reliability and accuracy of pipeline management through the sophisticated
application of contextual self-learning distributed artificial intelligence (AI) coupled with
strategically designed hybrid sensor arrays.
SUMMARY OF THE INVENTION
The Adaptive Intelligent Pipeline Integrity System (AIPIS) represents a substantial step
forward in pipeline monitoring technology. It achieves comprehensive oversight through
the strategic deployment and integration of sophisticated hybrid sensor arrays. Central to
its innovative operation is a contextual, self-learning distributed AI engine. This AI is
engineered to continuously adapt its understanding and predictions by analysing a
confluence of real-time sensor data, dynamic operational context, and fluctuating
environmental variables. A key feature of the invention is its employment of distributed
learning, processing information both locally at individual sensor nodes (“edge
processing”) and centrally. This distributed architecture is integral, offering tangible
benefits: reduced latency for critical event detection allows for faster responses;
minimized data bandwidth requirements make deployment more feasible, especially in
remote areas; improved power efficiency extends operational life for nodes relying on
battery or solar power; and enhanced overall system resilience is achieved, mitigating risks
associated with single points of failure in communication or central processing. By
analysing the diverse inputs from the hybrid array, the AI accurately detects leaks,
monitors the progression of corrosion, and identifies structural anomalies with a level of
precision surpassing prior capabilities. Crucially, the system’s inherent ability to correlate
disparate data streams and consider contextual factors dramatically minimizes false
alarms, ensuring that operators receive actionable, high-confidence alerts rather than
being inundated with ambiguous signals. This proactive approach, centred on predictive
maintenance, yields significant operational benefits, demonstrated by an estimated
reduction in inspection-related downtime by 40% compared to conventional inspection
schedules. AIPIS further includes integrated real-time visualization tools, remote
management functionalities, and automated response capabilities, providing a complete
pipeline integrity solution engineered for scalability across extensive networks and
designed to address practical deployment challenges such as remote power provision and
secure data communication.
Why It Matters
Pipelines are the lifelines of modern infrastructure, carrying water, oil, gas, and chemicals across vast distances. A single unnoticed failure can cause millions in damage within hours. With industries and governments increasingly focusing on sustainability, safety, and cost efficiency, this invention comes at the right time.
Key benefits include:
- Saving thousands of crores in infrastructure costs
- Reducing accident risks and environmental hazards
- Ensuring uninterrupted water and energy supply
- Supporting India’s smart infrastructure vision
What Maheep says:
Speaking about the approach behind the project, Maheep Purohit said, “Pipeline accidents not only cause financial losses but also pose a threat to life, property, and the environment. With AIPIS, our goal is to provide a system that can detect threats before they escalate. As a student, I take great pride in having been able to provide a solution that can have a national impact, save millions of rupees, reduce unplanned maintenance, and safeguard resources and communities.”
