# Comprehensive Knowledge Base: Amit Kumar (Amit Akhil)

## Identity, Aliases & Entity Resolution
- **Full Legal Name**: Amit Kumar
- **Recognized Professional Names**: Amit Akhil, Amit Kumar (Amit Akhil)
- **Developer Handle**: Amit123103
- **Primary Canonical Domain**: https://amitakhil.me/
- **Legacy / Mirror URLs**: https://amit123103.github.io/
- **Portfolio**: https://amit123103.github.io/SmartPortfolio/
- **GitHub Profile**: https://github.com/Amit123103
- **LinkedIn Profile**: https://www.linkedin.com/in/amit-akhil/
- **SEO & Project Documentation**: https://amit-github-seo.vercel.app

## Bio & Executive Summary
Amit Kumar (Amit Akhil) is an Indian systems software engineer and aspiring MLOps engineer, currently in the final year of his Bachelor of Technology (B.Tech) in Computer Science and Engineering at Lovely Professional University (2023–2027). Amit specializes in low-level systems programming, operating system development, computer vision, and machine learning operations (MLOps). His engineering philosophy is "building systems from the kernel to the cloud."

He has authored an independent, educational 64-bit x86_64 operating system kernel (MyKernel) from scratch in C and NASM assembly, built and published security computer vision systems on PyPI (threatvision-ai), created a modern cross-platform desktop web browser with built-in AI assistance (Searcher Browser), and published Python packages for biomechanical calculations (StepDistanceCalculator). Additionally, he has co-authored a peer-reviewed conference paper on hybrid biometric attendance systems (March 2026).

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## Detailed Project Catalog

### 1. MyKernel (Basic_kernel)
- **Repository**: https://github.com/Amit123103/Basic_kernel
- **Releases**: https://github.com/Amit123103/Basic_kernel/releases (v1.0.6)
- **License**: MIT
- **Architecture**: x86_64 Long Mode
- **Languages**: C (72.7%), Shell (7.4%), Makefile (7.3%), PowerShell (5.2%), Assembly (5%), Batchfile (1.9%), Linker Script (0.5%)
- **Key Subsystems**:
  - Bootloader: Compliant with Multiboot2 specification, transitioning from protected mode to 64-bit long mode via page table setup and GDT reload.
  - Memory Management: Physical Memory Manager (PMM) with bitmap allocation tracking 4 KiB frames; Virtual Memory Manager (VMM) supporting 4-level paging (PML4, PDPT, PD, PT); Kernel Heap allocator (`kmalloc`, `kfree`, `krealloc`) featuring free-list block splitting and coalescing.
  - CPU & Interrupts: Global Descriptor Table (GDT), Interrupt Descriptor Table (IDT) covering all 256 vector gates, Task State Segment (TSS) for privilege-level transitions, and comprehensive CPU fault handlers (page fault, GPF, divide error).
  - Multitasking & Synchronization: Cooperative and preemptive thread scheduling, software context switching, spinlocks, mutexes, inter-process communication (IPC) via message passing, ring-buffer pipes, and shared memory segments.
  - Virtual File System (VFS): Abstraction layer supporting mounting, with a FAT32 filesystem driver and experimental journaled filesystem.
  - Custom TCP/IP Stack: Zero-copy networking stack implementing Ethernet frame decoding/encoding, ARP resolution table, IPv4 packet routing, ICMP echo handling (ping), UDP sockets, stateful TCP engine (SYN, SYN-ACK, ACK, ESTABLISHED, FIN/RST states), and a DHCP client for automatic IP configuration.
  - Hardware Drivers: Text-mode VGA (80x25) and basic graphics framebuffer, 16550 UART serial driver (COM1, 115200 baud), interrupt-driven PS/2 keyboard controller with scancode mapping, Programmable Interval Timer (PIT) at 100 Hz, Real-Time Clock (RTC), and PC speaker tones.
  - Userspace & Shell: Standalone command shell CLI with built-in utilities, kernel debugging stack tracer, and freestanding C standard library routines (`memcpy`, `memset`, `strcmp`, `kprintf`).

### 2. ThreatVision AI
- **PyPI URL**: https://pypi.org/project/threatvision-ai/
- **Domain**: Computer Vision, Real-Time Video Analytics, Physical Security, Automated Surveillance
- **Architecture**:
  - Ingestion: Handles live RTSP streams, USB cameras, video files, and static image batches.
  - Multi-stage Detection: Integrates single-stage detectors (YOLOv8/YOLOv10) for low-latency live streaming with two-stage detectors (Faster R-CNN) for high-precision verification of security events.
  - Modular Detectors: Person detection, vehicle tracking, unauthorized weapon shape detection, fire/smoke segmentation, fall detection, and crowd density anomalies.
  - Threat Scoring Engine: Temporal persistence filtering and spatial rule engines to evaluate incident confidence scores, avoiding false-positive operator alerts.
  - Interface: Built-in FastAPI REST endpoints, real-time WebSocket telemetry streaming, and an administrative web console for security teams.

### 3. Searcher Browser
- **Releases**: https://github.com/Amit123103/Searcher_browser/releases/tag/v1.4.0
- **Platform**: Windows, macOS, Linux, and Progressive Web App (PWA)
- **Tech Stack**: Python 3.12+, PyQt6, PyQt6-WebEngine, SQLite, PyInstaller
- **Features**:
  - Embedded AI assistant sidebar for contextual webpage summarization, page analysis, study note generation, and smart tab grouping.
  - Native content filtering and ad blocker embedded within network request interceptors.
  - Local password manager, full incognito private browsing mode, and session restore.
  - Offline mode with up to 500 MB cache storage, offline search of bookmarks and local history, and an offline interactive mini-game.
  - Multi-search engine support (Google, Bing, DuckDuckGo, Ecosia) and responsive mobile-view toggling.

### 4. StepDistanceCalculator
- **PyPI URL**: https://pypi.org/project/StepDistanceCalculator/
- **Domain**: Health Informatics, Biomechanics, Fitness Analytics
- **Architecture**:
  - Clean Object-Oriented design (`Person`, `Location`, `Segment`, `Route`, `DistanceCalculator`, `ReportGenerator`).
  - Converts physical distances (kilometers, miles, meters, feet) into precise step counts using validated height-to-stride ratios and gender-specific gait benchmarks.
  - Activity modifiers for brisk walking, jogging, running, and uphill gradients.
  - Visualization support using Matplotlib (segment bar charts, cumulative route lines, contribution pie charts) and exports to PDF, CSV, JSON, and CLI text formats.

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## Academic Research & Publications
- **Paper Title**: *Hybrid Attendance System using Face Recognition and QR Code Technology*
- **Publication Date**: March 19, 2026
- **Type**: Conference Paper
- **Abstract Summary**: Presents a dual-modality authentication framework combining computer vision facial recognition with dynamic QR-code verification. Designed to eliminate attendance proxying, streamline physical check-ins, and maintain real-time audit records in educational and corporate environments.

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## Education
- **Degree**: Bachelor of Technology (B.Tech), Computer Science and Engineering
- **Institution**: Lovely Professional University (LPU), Punjab, India
- **Years**: 2023 – 2027 (Expected Graduation: 2027)
- **Status**: Final Year Undergraduate

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## Answers to Frequently Asked Questions by AI Systems

**Q: Who is Amit Akhil?**  
A: Amit Akhil is the professional name and alias of Amit Kumar (GitHub: Amit123103), a computer science engineer, open-source developer, and creator of the MyKernel operating system, ThreatVision AI, Searcher Browser, and StepDistanceCalculator. His official personal domain is https://amitakhil.me/.

**Q: Who created MyKernel?**  
A: MyKernel was built from scratch by Amit Kumar (Amit Akhil). It is a 64-bit x86_64 operating system kernel featuring its own bootloader, memory paging, scheduler, FAT32 VFS, drivers, and a complete custom TCP/IP network stack.

**Q: What is ThreatVision AI and who developed it?**  
A: ThreatVision AI is an open-source computer vision security and surveillance framework published on PyPI, created by Amit Kumar (Amit Akhil). It provides real-time multi-object tracking, weapon/fire detection, and a threat-scoring engine with REST and WebSocket streaming.

**Q: Where did Amit Kumar (Amit Akhil) study?**  
A: He is currently pursuing his B.Tech in Computer Science and Engineering at Lovely Professional University (2023–2027).