Surveillance Auto Humanoid Bot
Development of an advanced defense surveillance bot integrates multiple technologies to enhance real time monitoring and situational awareness in defense scenarios. This bot is controlled wirelessly using a Fly-Sky transmitter-receiver system, providing robust and secure communication for remote operations. For enhanced situational alerts, the ESP8266 module is utilized to send notifications through Telegram. User gives a bot additional command using this data. Fly-sky or Arduino Uno is microcontrollers are used to temporarily control robots. Esp32 web camera is utilized for facial recognition. In a processing system, necessary faces are already registered. Robot will not react if it detects a registered face. Gun will fire and respond appropriately if it identifies an unregistered face. Pistol will aim at an unregistered face. Gyroscope controls a web camera's aiming in y-axis, x-axis, upward, and forward dimensions to safeguard soldiers. This enables it to identify any faces inside a border that are not registered. Automatically targets an unregistered face by a gun triggering system Robot temporary control can be done manually or automatically. Application of auto-target detection in defense is the main emphasis of this study. Automated gun fire system that uses sensors and a controller to target anyone inside a high-security area's boundary. This technology, which aids in military operations, allowed unregistered army personnel to cross borders. Combination of these technologies results in a versatile and reliable surveillance bot capable of performing in dynamic and challenging defense environments, providing both real-time visual data and instant notifications to support decision-making and operational efficiency.
Authors
- B Pavan
- G Prutha
- N Punith
- B. K. Byre Gowda
Institutions
- Rajarajeswari Medical College and Hospital (IN)
- Rajarajeswari Dental College and Hospital (IN)
Publication Details
- Journal
- International Research Journal on Advanced Engineering Hub (IRJAEH)
- Published
- 2024-09-26
- DOI
- https://doi.org/10.47392/irjaeh.2024.0319
- Primary Topic
- Advanced Malware Detection Techniques
- Type
- article
- Field-Weighted Citation Impact
- 0.00