SmartInspect AI: AI-Driven System for Secure Fire Safety Inspection and NOC Automation
Sahil Kavatkar
Department of
Computer Engineering
Atharva College of
Engineering, Mumbai,
India
sahilkavatkar-cmpn@atharvacoe.ac.in
Amit Gupta
Department of
Computer Engineering
Atharva College of
Engineering, Mumbai,
India
amitgupta-cmpn@atharvacoe.ac.in
Sagar Mandigam
Department of
Computer Engineering
Atharva College of
Engineering, Mumbai,
India
sagarmandigam-cmpn@atharvacoe.ac.in
Suraj Mandigam
Department of
Computer Engineering
Atharva College of
Engineering, Mumbai, India
surajmandigam-cmpn@atharvacoe.ac.in
Prof, Pranali Bhusare
Asst. Professor
Department of
Computer Engineering
Atharva College of
Engineering, Mumbai,
India
parnalibhusare@atharvacoe.ac.in
Abstract: The traditional Fire No Objection Certificate (NOC) inspection process is largely manual, time-consuming, and prone to errors and data manipulation, which can compromise public safety. This paper presents SmartInspect AI, an intelligent and secure inspection system that leverages Artificial Intelligence and sensor-based validation to modernize fire safety compliance. The proposed system integrates geo-tagging, timestamp verification, barometric floor detection, perceptual image hashing, and audio-based fire alarm verification to ensure authenticity and reliability of inspection data. A mobile application enables field officers to capture real-time evidence, while a centralized backend processes and stores the data securely, and an administrative dashboard facilitates efficient monitoring and decision-making. By introducing tamper-proof data collection and multi-layered verification, the system enhances transparency, reduces fraud, and accelerates the NOC approval process. The solution is scalable, cost-effective, and aligned with smart governance initiatives such as Digital India, making it a practical approach for improving fire safety inspection systems.
A mobile application is used by field officers to capture real-time inspection data, while a centralized backend processes and stores the information securely. Additionally, an administrative dashboard enables authorities to review structured data and make informed decisions efficiently by introducing tamper-proof data collection and AI-assisted validation, the proposed system reduces fraud, enhances accountability, and accelerates the NOC approval process. The solution is scalable, cost-effective, and aligned with smart governance initiatives such as Digital India and Smart Cities.
Keywords: Fire Safety, Artificial Intelligence, Image Hashing, Geo-Tagging, Audio Analysis, Smart Inspection, NOC Automation
