InnoCore Labs

Trilobe Mark-II is an unmanned combat vehicle designed and developed at UEMJ by Afaq Ahmad. The system is built to operate remotely using wireless connectivity, enabling communication with a command center for control and monitoring. It is equipped with an integrated solar charging system, allowing the vehicle to recharge its battery pack in remote or off-grid locations, enhancing operational endurance.

The vehicle is powered by a lithium-ion battery pack, selected for its high energy density, lightweight nature, and fast charging capability. In addition to conventional charging, the system includes dual solar panels mounted in a foldable configuration to optimize space. These panels are connected in series to increase power output, providing approximately 12V DC at 0.8–1 Amp for auxiliary charging.

A key feature of Trilobe Mark-II is its digitally controlled missile ignition system, capable of launching up to 40 missiles on a single charge. The ignition system is designed for reliability and low maintenance, using advanced electronic control through relay and high-voltage driver modules. The firing mechanism supports both manual and automatic modes, with adjustable angle of projection and safety indications for armed and disarmed states.

The vehicle also incorporates a drone station, enabling aerial surveillance and real-time monitoring of target areas. This enhances situational awareness by providing a broader field of vision and aiding in enemy detection and tracking.

Additional features include high-brightness front-mounted LEDs for improved night visibility and robust electronic control systems for motor and weapon operations. Overall, Trilobe Mark-II represents a combination of mobility, remote operation, renewable energy integration, and advanced combat capabilities, making it a versatile and efficient unmanned defense platform.

The Smart Garden Light is an IoT-based system developed by AiT UEMJ to automate and monitor garden lighting and irrigation. It integrates sensors, a microcontroller, and a relay unit to provide intelligent control based on real-time environmental conditions.

The system uses a light sensor to automatically switch garden lights ON during nighttime and OFF during daytime. A soil moisture sensor continuously monitors soil conditions and activates the irrigation system when water levels fall below a defined threshold. This ensures efficient water usage and optimal plant care.

Users can control and monitor the system remotely through an Android application connected via an IoT network. The application provides features such as manual ON/OFF control, timer-based operation, pump control, soil moisture monitoring, and an autonomous mode for fully automated functioning.

Overall, the Smart Garden Light system enhances convenience, energy efficiency, and plant health by combining automation, IoT connectivity, and smart sensing technologies.

The Smart IV Drip Monitoring Device is an intelligent healthcare solution designed to continuously monitor intravenous (IV) fluid flow and improve patient safety in hospitals and clinical environments. The system combines sensor-based monitoring, microcontroller processing, and a real-time dashboard to ensure accurate tracking of IV parameters and timely alerts.

The device utilizes sensors to measure drip rate, detect fluid levels, and identify flow irregularities such as blockage, air bubbles, or an empty IV bottle. When any abnormal condition is detected, the system instantly triggers alerts through visual indicators, buzzer notifications, and dashboard warnings, enabling healthcare staff to respond quickly and effectively.

At the core of the system is a microcontroller (such as ESP32), which processes real-time data from sensors and transmits it over an IoT network to a centralized monitoring dashboard. The dashboard provides a live overview of multiple patients simultaneously, displaying key parameters like drip rate, fluid status, and alert conditions. This significantly reduces the need for manual monitoring and allows medical staff to manage multiple IV setups efficiently.

The system also supports advanced features such as threshold-based alerts, historical data tracking, and remote access, ensuring better decision-making and improved patient care. Its ability to provide continuous monitoring minimizes human error and enhances response time in critical situations.

Designed to be compact and easy to integrate with existing IV systems, the device operates on low power and can be powered using rechargeable batteries, ensuring reliability even during power interruptions.

Overall, the Smart IV Drip Monitoring Device enhances healthcare efficiency, safety, and automation by integrating real-time sensing, intelligent alerting, and centralized dashboard control, making it a valuable innovation for modern medical systems.

A smart system that tracks machine runtime and activity cycles to measure productivity, reduce idle time, and improve operational efficiency

The Time-Based Work Done Monitoring System is an advanced embedded solution developed to accurately quantify machine productivity by analyzing operational time, activity cycles, and utilization patterns in real-time. Unlike conventional monitoring systems that rely solely on instantaneous parameters, this system focuses on time-driven performance evaluation to provide a more reliable measure of actual work done.

The device continuously monitors machine states using sensor inputs (such as proximity sensors, current sensors, or vibration feedback) to detect whether the machine is actively performing work, idling, or completely stopped. Based on these inputs, the system classifies operation into distinct states—Active Run Time, Idle Time, and Downtime—and logs each with high precision.

A core algorithm processes this time-segmented data to calculate effective work done over a defined period. By assigning weighted significance to active cycles and filtering out non-productive intervals, the system generates meaningful productivity metrics such as utilization percentage, effective working hours, and cycle efficiency.

The system features an embedded microcontroller-based architecture with real-time processing capability, enabling immediate feedback through OLED/LCD displays. It can also store historical data for trend analysis and performance auditing. Optional alert mechanisms notify operators when machine utilization drops below predefined thresholds, ensuring timely corrective action.

Designed for industrial environments, the solution is robust, scalable, and easily integrable with existing machinery. It plays a critical role in improving operational transparency, optimizing workforce and machine usage, supporting preventive maintenance strategies, and ultimately enhancing overall production efficiency.