The Smart Systems & Energy Lab (SSEL) at SINES focuses on cutting-edge research in renewable energy harvesting systems, self-powered sensors, embedded systems, and smart systems applications. Our work integrates interdisciplinary fields such as systems engineering, embedded IoT systems, and artificial intelligence to develop sustainable solutions for real-time monitoring and precision agriculture.

Dr. Muhammad Iqbal, Assistant Professor at SINES, NUST, specializes in energy harvesting, renewable energy technologies, self-powered sensors, IoT systems, and artificial intelligence. My research interests include the design and development of smart systems for sustainable energy applications, with a focus on wearable electronics, health monitoring, and structural health monitoring.

PI’s Profile:

Dr. Muhammad Iqbal, Assistant Professor at SINES, NUST, specializes in energy harvesting, renewable energy technologies, self-powered sensors, IoT systems, and artificial intelligence. My research interests include the design and development of smart systems for sustainable energy applications, with a focus on wearable electronics, health monitoring, and structural health monitoring.

Lab Equipment/Resources:

• Since the lab is newly established, we don’t have equipment yet. The following equipment will be required as part of the lab setup.
• Energy harvesting components (electromagnetic, piezoelectric, triboelectric and hybrid)
• Micro and nano fabrication equipment
• IoT development kits and sensors
• Embedded systems platforms (e.g., Raspberry Pi, Arduino)
• Data acquisition and analysis tools (e.g., COMSOL Multiphysics, LabVIEW, DAC Card)
• Specialized equipment for renewable energy research (e.g., wind and vibration energy harvesting setups)

Projects:

1. Development of Novel Surveillance Unmanned Ground Vehicle for Crop Health Monitoring (Co-Principal Investigator, PKR 3.5 million)
2. Several ongoing PhD and MS projects related to energy harvesting, smart agriculture, and healthcare applications.

Human Rersource:

Typical Enrollment of lab researchers: 8-10 MS/PhD researchers

Expertise/Capablities of Lab:

1. Energy Harvesting: Expertise in piezoelectric, electromagnetic, triboelectric and hybrid energy harvesting systems.
2. Renewable Energies: Focus on sustainable power solutions for IoT systems, wearable electronics, and remote sensing.
3. Smart Systems & IoTs: Design and development of embedded IoT systems for agricultural and healthcare applications.
4. AI & Machine Learning: Application of AI, deep learning, and data analytics for sensor data interpretation, system optimization, and predictive maintenance.
5. Structural Health Monitoring: Development of self-powered sensors for monitoring infrastructure and machinery health.

Research Focus:

1. Self-Powered Sensors & Energy Harvesting
   o Biomechanical, vibration, wind, and acoustic energy harvesting.
   o Piezoelectric, electromagnetic, and triboelectric conversion mechanisms.
   o Hybrid harvesting solutions for reliable off-grid and portable applications.
   o Intelligent strategies for efficient energy capture, storage, and utilization.
   o Development of self-sustaining IoT nodes for real-time monitoring.
2. AI-Embedded IoTs
   o Edge and embedded AI for real-time analytics
   o AI-driven smart agriculture, water, and environmental monitoring
   o Machine learning for predictive maintenance and anomaly detection
3. Structural Health Monitoring (SHM)
   o IoT-enabled monitoring for buildings, bridges, and critical infrastructure.
   o Non-invasive sensing using vibration, strain, and imaging techniques.
   o Data-driven predictive models for early fault detection and safety assurance.
4. Hyperspectral Imaging & Smart Sensing
   o Food safety, agriculture, and pharmaceutical quality assessment.
   o Non-destructive monitoring for milk, crops, and medicine.
   o Imaging-assisted energy and environmental monitoring.
   o AI integration for intelligent decision-making and real-time analytics

Contact Us:

Dr. Muhammad Iqbal
Contact No.: 5190855746
Email: [email protected]