Storm Schutte

Space In Lost - Jupiter J2

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Gallery

AI Weapon Detection System

Deep Learning Project

Developed a novel weapon detection model leveraging Deep Learning to contribute towards public safety. This project involved identifying nine different types of weapons with an impressive F1 score of 83.3%. The model was trained on a comprehensive dataset comprising 52,000 weapon image files, achieved through data augmentation techniques.

The model was architectured around Convolutional Neural Networks (CNN), a proven deep learning algorithm known for its efficacy in image recognition tasks. Testing was conducted across diverse mediums including CCTV footage, movie scenes, still pictures, and live videos to ensure functionality across real-world scenarios.

The primary objective is to fortify security measures in public spaces by enabling real-time weapon detection. This project showcases the transformative role of AI in bolstering security and maintaining societal harmony through intelligent surveillance systems.

AI Gunfire Detection System

Emergency Alert Project

Developed an audio classification model to address the alarming rise in school shootings in the USA. The project focuses on recognizing and differentiating between various sounds, with primary emphasis on detecting gunshots and alerting designated individuals via email.

The model utilizes a large dataset of audio files featuring ambient noise, construction sounds, barking, sirens, horns, and gunshots. Built on CNN architecture with ReLU activation function and Adam optimizer, the system processes audio using powerful libraries like TensorFlow, Keras, and Librosa.

The project includes real-time alert mechanisms that automatically send emails when emergency sounds are detected, demonstrating practical application in increasing security and enabling rapid responses to critical situations.

Tag9 Data Collection Platform

Full-Stack Application

Tag9 is an innovative, cutting-edge application designed to revolutionize the process of creating, sharing, and collecting data through customizable forms. The application combines ease of use, versatility, and robust security features to provide an unparalleled solution for businesses and organizations.

Key features include flexible form creation with a user-friendly interface, efficient data sharing via QR codes or tokens, comprehensive data collection with advanced security measures, and seamless integration capabilities with existing software systems.

Built using the robust Django web framework, backed by PostgreSQL database, and enhanced with JavaScript for intuitive user experience. The platform ensures data security with state-of-the-art measures while maintaining the highest standards of privacy and compliance.

PEIMS Academy Management System

Educational Platform

PEIMS academy management system allows for comprehensive management of different academies, from class management to customer financial tracking, in-class management, and staff/student administration. The system was designed to be suitable for as many academy types as possible.

The platform focuses on essential and important features needed for effective academy operations. It provides tools for academy class management, customer financial management, in-class management, and comprehensive staff and student management systems.

Built with Django framework, the system offers scalable solutions for educational institutions seeking efficient management tools. More information available at: https://www.peims.co/more_on_peims_academy_management_system/

Intelligent Testing System (ITS)

Korean Government Project

An intelligent testing system developed for the Korean Government that revolutionizes traditional examination methods. The system uses advanced algorithms to dynamically adjust questions based on individual performance throughout the exam.

The application employs sophisticated parameters and algorithms that analyze the test-taker's responses in real-time, adapting the difficulty and type of questions to match their skill level and learning progress.

This adaptive testing approach provides more accurate assessments while creating personalized examination experiences. The system represents a significant advancement in educational technology and assessment methodologies.

SunSeo Audio Player App

Mobile Application

A cross-platform mobile application developed for both Android and iPhone platforms. The app was specifically designed for a business that needed audio files to be accessible to their members through a dedicated mobile application.

The application features a custom audio player interface, secure content delivery, and user authentication systems to ensure only authorized members can access the audio content.

The project showcased expertise in cross-platform mobile development, delivering a professional solution that met the specific business requirements for secure audio content distribution to members.

AI Pothole Detection System

Computer Vision Project

This project involved developing a computer vision pipeline to detect and count potholes on city roads in real time. The solution was designed for a municipal client who required an automated system to quantify road surface damage across different regions.

A forward-facing camera was mounted on vehicles to continuously capture road footage. The video stream was processed by a custom deep learning model that I architected and trained from scratch. The model was based on a convolutional neural network (CNN) optimized for object detection in challenging outdoor environments with variable lighting and road conditions.

The workflow included data acquisition and labeling of pothole images with manual annotation of bounding boxes, model development using a self-built CNN tailored for pothole detection with transfer learning techniques, and implementation of a video processing pipeline that ingests live footage, runs frame-by-frame detection, and outputs pothole counts with minimal latency.

The system achieved 98% detection accuracy with near-zero false positives, validated on unseen test data and field trials. The system proved highly effective in automating road condition monitoring, significantly reducing manual inspection requirements and enabling data-driven decision making for city infrastructure maintenance.

Smart Home IoT Device

IoT & Edge AI Platform

This project focused on building a smart home IoT device designed to integrate environmental sensing, user interaction, and health monitoring into a unified intelligent system. The platform was developed on a Raspberry Pi running Ubuntu Server, serving as the central hub for data collection, processing, and device orchestration across the home.

Key Features: Voice Interaction & Natural Language Understanding - Distributed microphone arrays across the home enabled real-time audio capture. Integrated a natural language processing (NLP) pipeline to interpret user commands and questions. Connected to OpenAI's language models to provide conversational responses and execute tasks.

Home Automation & Device Control - Wireless modules (Wi-Fi based) allowed seamless integration with smart devices including lighting, automatic curtains, speakers, and alarm systems. Commands could trigger automated environmental adjustments or notifications, creating a fully responsive smart home environment.

Health Monitoring (Prototype Component) - Designed a biometric monitoring module to continuously track breathing, heart rate, perspiration, and movement. The objective was to support individuals with chronic health conditions by providing real-time wellness tracking and alerts.

System Architecture - Modular IoT framework combining real-time data ingestion, event-driven processing, and device control. Edge-computing setup on Raspberry Pi for low-latency operations, with cloud-assisted AI inference for natural language understanding.

Results & Impact: The system successfully demonstrated real-time multimodal interaction (voice + environment + health monitoring). It is currently deployed in several homes, where it provides automated control, conversational assistance, and adaptive responses to user behavior. While the health monitoring component remained in prototype stage, the core system proved reliable in real-world environments.

Full-Stack Web Application and Scalable Systems Architecture

Web Development & Cloud Architecture

Since 2007, I have developed and deployed over 100 websites spanning corporate, non-profit, educational, and personal domains. My experience covers the full lifecycle of web application development, from frontend design to backend architecture, infrastructure management, and deployment at scale.

Technologies & Frameworks: Frontend - HTML, CSS, React, and JavaScript frameworks for building responsive and user-centric interfaces. Backend - PHP, Python (Django/Flask), Node.js, and custom API development for dynamic content delivery and integration. Cloud & Hosting - Extensive deployment experience across AWS (Elastic Beanstalk, EC2, Amplify), Google Cloud Platform, Cloudflare, PythonAnywhere, and Heroku. Also deployed custom solutions on Microsoft servers and local self-hosted environments.

Types of Solutions Built: Corporate Websites - Developed scalable websites for organizations of 100+ employees, with features supporting internal operations, client communication, and data visualization. CRM & Enterprise Platforms - Built full-featured systems for academies, stock-trading platforms (with real-time tracking and scoring mechanisms), and multi-functional enterprise portals to streamline operations. Community & Global Platforms - Created international websites with multi-language support, communication hubs, and real-time collaboration tools. NGO and Pro-Bono Work - Designed and hosted websites for non-profits, ensuring cost-effective yet high-quality digital presence.

Architecture & Deployment: Implemented modular architectures to support integration of blogs, forums, trading dashboards, and monitoring systems. Leveraged cloud-native practices (CI/CD pipelines, load balancing, distributed hosting) to ensure reliability and scale. Applied DevOps principles for deployment automation and performance optimization.

Impact: These projects have supported diverse use cases, from small-scale informational websites to mission-critical systems serving international audiences. My long-term practice in web technologies has given me deep expertise in scalable architectures, cross-platform deployment, and secure, data-driven applications.