Full-stack development, IoT systems, mobile apps, and custom software engineering. Turning complex problems into elegant solutions.
Comprehensive solutions from concept to deployment
Cross-platform iOS and Android applications using React Native, Flutter, and native technologies.
Responsive, modern web applications with focus on UX, performance, and scalability.
Creative branding solutions that communicate your vision and values effectively.
Custom IoT solutions using Raspberry Pi, Arduino, microcontrollers, and sensor networks.
Showcase of engineering and development work
Digital railway inspection platform replacing manual paper-based systems with cloud-connected Android app.
AI-powered financial portfolio analyzer with predictive market insights, risk assessment, and comprehensive BSE stock analysis.
IoT-based intelligent autonomous vehicle with remote control via Android app, obstacle detection, lane following, and traffic signal recognition.
I'm a solutions engineer with expertise in full-stack development, IoT systems, and digital product design. With a background in both software and hardware engineering, I bridge the gap between digital and physical systems.
Specializing in Raspberry Pi, microcontrollers, and embedded systems
Custom solutions using Raspberry Pi for automation, monitoring, and control systems.
Design and implementation of wireless sensor networks for data collection and analysis.
Smart automation for homes, offices, and industrial applications with remote control.
Connecting IoT devices to cloud platforms for data storage, processing, and visualization.
Ready to bring your engineering project to life?
support@amazexplorelabs.com
+91 (7208) 688-604
Mumbai, India
Central Railway's traditional inspection system relied entirely on manual paper-based records. Inspectors carried physical logbooks, filled out forms by hand, and maintained files in storage rooms, leading to:
CRInspection transforms the entire inspection workflow into a digital ecosystem with:
Built with Kotlin and Android Jetpack for optimal performance on field devices
Real-time data sync to secure AWS cloud servers with offline capability
Quick asset identification and instant access to maintenance history
Customizable templates for different asset types with validation rules
Continue inspections in remote areas with automatic sync when online
Time-stamped, geo-tagged images with automatic compression
Web portal for supervisors with real-time visualization tools
The CRInspection app has revolutionized how we conduct safety checks. What used to take days now happens in minutes, and we can actually prevent issues instead of just reporting them.
Interested in a similar digital transformation solution for your organization?
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Developed as a Master's professional project, FinOptima addresses the critical need for intelligent portfolio management tools that combine real-time market data with AI-driven predictive analytics. The platform empowers investors with:
Interactive visualization of asset allocation, performance tracking, and diversification analysis with real-time updates
Machine learning models predicting bullish/bearish trends for all BSE stocks with 95% accuracy
Dynamic risk assessment tool calculating portfolio volatility, market risk, and personalized risk scores
Personalized investment suggestions based on risk profile, market conditions, and financial goals
Real-time BSE/NSE data feeds, historical data APIs, and financial news aggregation
LSTM neural networks for trend prediction, sentiment analysis NLP models
Risk calculation, portfolio optimization algorithms, performance metrics
Interactive visualizations, real-time updates, and actionable insights
Time-series prediction model analyzing historical stock patterns to forecast bullish/bearish trends with 92-96% accuracy across different market conditions.
Natural Language Processing model analyzing financial news, social media, and earning calls to gauge market sentiment and predict short-term movements.
Proprietary algorithm calculating dynamic risk scores based on portfolio composition, market volatility, and macroeconomic factors.
The Riskometer provides a visual representation of portfolio risk calculated using multiple factors:
Updates in real-time based on market movements and portfolio changes.
Real-time tick data for 5,000+ stocks with 15-minute delay for free tier
10+ years of OHLC data for technical analysis and backtesting
Aggregated from Reuters, Bloomberg, Economic Times, and 12+ sources
Inflation rates, GDP growth, interest rates, and forex data
Genetic algorithms for optimal asset allocation and tax-efficient investing strategies
Native iOS/Android apps with push notifications for critical market movements
Secure transaction recording and decentralized portfolio management
FinOptima represents an exceptional implementation of machine learning in financial analytics. The integration of LSTM networks for market prediction combined with comprehensive risk assessment demonstrates advanced understanding of both AI principles and financial markets.
Interested in implementing AI-driven financial solutions or data analytics platforms?
Discuss Financial Tech Solutions
AutoDriveX is a comprehensive IoT-based autonomous vehicle system that combines remote manual control with intelligent autonomous capabilities. The system features a three-tier architecture:
User interface for remote control with real-time video streaming, command transmission, and system monitoring
Central command and control server processing requests, managing connections, and storing telemetry data
Raspberry Pi-based vehicle with 4G connectivity, computer vision, and motor control systems
Real-time control via Android app with <50ms latency using WebSocket protocol
Computer vision-based autonomous driving with multiple AI models
4G SIM-based always-connected system with cloud synchronization
Main processing unit running all computer vision and control algorithms
8MP camera for computer vision processing
1080p @ 30fpsSIM800L module for cellular internet connectivity
150Mbps downloadHC-SR04 sensors for obstacle detection
2cm - 400cm rangeL298N dual H-bridge for DC motor control
2A per channel30 FPS video capture from Pi Camera
~5msGrayscale conversion, Gaussian blur, Canny edge detection
~8msHough transform for line detection and lane estimation
~12msHaar cascades for traffic signs and obstacle detection
~15msControl algorithm based on detected objects and lanes
~5msFor lane boundary detection with adaptive thresholding
edges = cv2.Canny(gray, 50, 150)
Line detection for lane marking identification
lines = cv2.HoughLinesP(edges, 1, np.pi/180, 50)
For traffic sign and signal detection
signs = cascade.detectMultiScale(gray, 1.1, 4)
Main control loop integrating all subsystems
Computer vision algorithms for autonomous driving
PWM-based motor speed and direction control
WebSocket client for cloud communication
Real-time communication between app and vehicle
Process and route control commands
RTMP streaming server for live video
Joystick and button control interface
Live video streaming viewer
Real-time communication handler
WiFi/4G → WebSocket → AWS Server
WebSocket Server + RTMP Streaming
4G SIM → WebSocket Client
Real-time control commands (50ms latency)
ws://server:8080/control
Live video streaming from vehicle
rtmp://server:1935/live/vehicle1
Telemetry data (battery, speed, GPS)
mqtt://server:1883/telemetry
Challenge: Maintaining responsive control over cellular networks
Solution: Implemented WebSocket with message compression and predictive movement
Challenge: Limited processing power on Raspberry Pi for CV algorithms
Solution: Optimized OpenCV with NEON optimizations and multi-threading
Challenge: Limited battery life with multiple sensors
Solution: Implemented sleep modes and power-efficient components
Watch the complete demonstration video showing all features in action:
Integration with OpenStreetMap for waypoint navigation
YOLO-based object detection for better accuracy
Control multiple vehicles from single interface
Offload complex processing to cloud servers
Interested in IoT, robotics, or computer vision solutions?
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