NoIR Camera Based Security Surveillance System

The NoIR Camera-Based Raspberry Pi Security system is an adaptive, intelligent security system that provides efficient, low-light monitoring. It reduces false alarms by using infrared sensitivity to provide day-and-night monitoring with advanced motion detection that can differentiate between objects, including people and animals. This technology is ideal for home security, animal tracking, and restricted access surveillance because it uses local, on-device processing to ensure data privacy, real-time responsiveness, and IoT integration for remote moni- toring. TensorFlow, which is adapted to run on the Raspberry Pi with TensorFlow Lite, is used in this system for object detection and identification. Effective edge processing is made possible by TensorFlow’slightweight models, which are essential for reducing latency and optimizing data privacy. Effective surveillance in low light and at night is made possible by the combination of NoIR imaging with AI-driven object detection. Future developments involve building a scalable network for wider industrial use, extending classification categories and using advanced facial recognition. Adaptability and security characteristics could be further enhanced with more cloud analytics and a deeper IoT integration.

Authors

Publication Details

Published
2025-04-15
DOI
https://doi.org/10.38124/ijisrt/25apr589
Citations
1
Primary Topic
Currency Recognition and Detection
Type
article
Field-Weighted Citation Impact
1.28
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

NoIR Camera Based Security Surveillance System

Sri Kalyan Yarlagadda, Niharika Nalluru, Santhi Swaroop Tirumalasetti, Mounika Uppuluri et al.
1 citations
Currency Recognition and Detection
1.28
article

NoIR Camera Based Security Surveillance System

Sri Kalyan Yarlagadda, Niharika Nalluru, Santhi Swaroop Tirumalasetti, Mounika Uppuluri, AnilKumar Akhil Perumprath
article en
1 citations

Abstract

The NoIR Camera-Based Raspberry Pi Security system is an adaptive, intelligent security system that provides efficient, low-light monitoring. It reduces false alarms by using infrared sensitivity to provide day-and-night monitoring with advanced motion detection that can differentiate between objects, including people and animals. This technology is ideal for home security, animal tracking, and restricted access surveillance because it uses local, on-device processing to ensure data privacy, real-time responsiveness, and IoT integration for remote moni- toring. TensorFlow, which is adapted to run on the Raspberry Pi with TensorFlow Lite, is used in this system for object detection and identification. Effective edge processing is made possible by TensorFlow’slightweight models, which are essential for reducing latency and optimizing data privacy. Effective surveillance in low light and at night is made possible by the combination of NoIR imaging with AI-driven object detection. Future developments involve building a scalable network for wider industrial use, extending classification categories and using advanced facial recognition. Adaptability and security characteristics could be further enhanced with more cloud analytics and a deeper IoT integration.

Openalex Percentile: Top 21%
Currency Recognition and Detection
1.28
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.