Research & Prototyping | Hexcode Plus R&D

Research Methodology Framework

Our research laboratories operate on a four-phase systems engineering workflow designed to transition concepts from theoretical analysis to production-ready prototypes. Each research track follows IEEE standards for documentation, validation, and verification.

PHASE 1: ANALYSIS

Requirements specification, constraint analysis, literature review, and feasibility assessment using industry-standard methodologies.

PHASE 2: DESIGN

Architecture definition, component selection, simulation modeling, and circuit/system-level design using CAD/EDA tools.

PHASE 3: IMPLEMENTATION

PCB fabrication, firmware development, integration testing, and iterative debugging to achieve functional specifications.

PHASE 4: VALIDATION

Performance benchmarking, stress testing, compliance verification, and comprehensive documentation generation.

Research Track 01

Embedded Systems Engineering

ACTIVE LABORATORY PROJECT

Real-Time Operating Systems (RTOS)

Research into deterministic task scheduling, inter-process communication, and memory management for embedded platforms. Focus on FreeRTOS kernel configuration for ARM Cortex-M microcontrollers.

RESEARCH OBJECTIVES:

→ Task prioritization algorithms for multi-threaded embedded applications
→ Interrupt latency optimization in real-time systems
→ Power-aware scheduling for battery-operated devices
→ Mutex and semaphore implementation for resource sharing

Platform: STM32, ESP32, Arduino

Languages: C, C++, Assembly

Tools: Keil, IAR, PlatformIO

Low-Power Embedded Design

Investigation of power optimization techniques for battery-powered and energy-harvesting embedded systems. Emphasis on sleep mode implementation and dynamic voltage scaling.

RESEARCH OBJECTIVES:

→ Ultra-low power microcontroller selection and configuration
→ Energy-efficient communication protocol design
→ Duty-cycle optimization for sensor networks
→ Power consumption profiling and analysis

Target: <1mA Average Current

Battery Life: >1 Year (CR2032)

Techniques: Sleep Modes, DVS, Clock Gating

Bootloader Development

Custom bootloader implementation for field-programmable embedded systems. Research into secure firmware update mechanisms and fail-safe recovery protocols.

RESEARCH OBJECTIVES:

→ Over-the-air (OTA) firmware update architecture
→ Cryptographic signature verification for secure boot
→ Dual-bank flash memory management
→ Rollback mechanisms for failed updates

Update Methods: OTA, UART, USB

Security: AES-256, RSA Signature

Sensor Fusion Algorithms

Integration of multiple sensor inputs using Kalman filtering and complementary filter techniques. Applications in motion tracking and environmental monitoring.

RESEARCH OBJECTIVES:

→ IMU data fusion (accelerometer, gyroscope, magnetometer)
→ Extended Kalman Filter (EKF) implementation
→ Noise reduction and outlier detection
→ Real-time orientation estimation

Sensors: MPU6050, BMP280, HMC5883L

Accuracy: ±2° orientation error

Research Track 02

IoT Infrastructure

ACTIVE LABORATORY PROJECT

MQTT Protocol Implementation

Design and deployment of scalable MQTT broker architecture for industrial IoT applications. Focus on Quality of Service (QoS) levels and message persistence.

RESEARCH OBJECTIVES:

→ Private MQTT broker configuration (Mosquitto, HiveMQ)
→ TLS/SSL encryption for secure communication
→ Topic hierarchy design for scalable deployments
→ Load testing and performance benchmarking

Protocol: MQTT v3.1.1 / v5.0

QoS Levels: 0, 1, 2 (Exactly Once)

Edge Computing Architecture

Distributed computing frameworks for edge devices to reduce cloud latency and bandwidth. Research into lightweight containerization and edge AI inference.

RESEARCH OBJECTIVES:

→ Edge node resource optimization (CPU, RAM, Storage)
→ Local data preprocessing and aggregation
→ Containerized edge applications (Docker)
→ Fog computing topology for hierarchical processing

Platforms: Raspberry Pi, NVIDIA Jetson

Frameworks: TensorFlow Lite, Node-RED

LoRaWAN Sensor Networks

Long-range, low-power wireless sensor networks for agricultural and industrial monitoring. Implementation of LoRaWAN gateways and network server infrastructure.

RESEARCH OBJECTIVES:

→ Multi-hop mesh network topology
→ Adaptive data rate (ADR) optimization
→ Gateway deployment for urban/rural coverage
→ Integration with The Things Network (TTN)

Range: Up to 15km (Line of Sight)

Frequency: 865-867 MHz (IN865)

Cloud Integration Platforms

Seamless integration with AWS IoT Core, Azure IoT Hub, and Google Cloud IoT for enterprise-grade telemetry and device management.

RESEARCH OBJECTIVES:

→ Device provisioning and authentication
→ Real-time data streaming pipelines
→ Cloud-based rule engines and alerts
→ Data visualization dashboards

Clouds: AWS, Azure, GCP

Protocols: MQTT, HTTP/S, WebSockets

Research Track 03

VLSI Design

RESEARCH TRACK

FPGA-Based Digital Design

Hardware description language (HDL) implementation of custom digital circuits on Xilinx and Altera FPGAs. Focus on high-speed signal processing and hardware acceleration.

RESEARCH OBJECTIVES:

→ Finite State Machine (FSM) design and optimization
→ Pipelined datapath architecture
→ Clock domain crossing (CDC) techniques
→ IP core integration and customization

Languages: Verilog, VHDL, SystemVerilog

Tools: Vivado, Quartus Prime

Digital Signal Processing (DSP)

Implementation of DSP algorithms in hardware for audio processing, image filtering, and communication systems. Use of specialized DSP blocks in FPGAs.

RESEARCH OBJECTIVES:

→ FIR/IIR filter implementation
→ Fast Fourier Transform (FFT) cores
→ Fixed-point arithmetic optimization
→ Real-time signal processing pipelines

Research Track 04

Robotics

ACTIVE LABORATORY PROJECT

Autonomous Navigation Systems

Path planning algorithms, obstacle avoidance, and SLAM (Simultaneous Localization and Mapping) for mobile robots using sensor fusion.

RESEARCH OBJECTIVES:

→ Ultrasonic and LIDAR-based mapping
→ A* and Dijkstra pathfinding algorithms
→ PID controller tuning for motor control
→ Computer vision for object detection

Robotic Manipulator Control

Kinematics and dynamics of robotic arms. Inverse kinematics solutions for pick-and-place applications and trajectory planning.

RESEARCH OBJECTIVES:

→ Forward and inverse kinematics modeling
→ Servo-based multi-axis control
→ Gripper design and force feedback
→ ROS (Robot Operating System) integration

Research Track 05

Software Engineering

ACTIVE LABORATORY PROJECT

Full-Stack Web Development

Modern web application architecture using JavaScript frameworks, RESTful API design, and database management for IoT dashboards and control panels.

RESEARCH OBJECTIVES:

→ Real-time data visualization (WebSockets, Chart.js)
→ Progressive Web Apps (PWA) for embedded systems
→ MongoDB/PostgreSQL for time-series data
→ Node.js backend for IoT data aggregation

Machine Learning for IoT

Deployment of lightweight ML models on edge devices for predictive maintenance, anomaly detection, and sensor data classification.

RESEARCH OBJECTIVES:

→ TensorFlow Lite model quantization
→ On-device inference optimization
→ Time-series forecasting for sensors
→ Edge AI hardware accelerators