The Smart Agri Tech Research Lab at SINES, NUST is at the forefront of developing cutting-edge technologies for smart agriculture. The lab specializes in creating AI-driven solutions for precision farming, crop health monitoring, yield optimization, and resource-efficient management. With expertise in real-time video analytics, IoT integration, and machine learning, the lab addresses challenges in modern agriculture through innovative hardware and software systems. Its capabilities include advanced sensor design, edge AI, real-time data analytics, and scalable IoT platforms. Equipped with state-of-the-art resources such as PCB prototyping tools, embedded edge devices, and GPUs, the lab supports comprehensive research and development. Current projects focus on solar-powered silo monitoring, disease detection in livestock, and multi-sensor data fusion. With a team comprising Ph.D. scholars, research associates, and postdoctoral fellows, the lab drives impactful research to revolutionize agricultural practices and promote sustainability.

PI’s Profile:

Dr. Shahzad Younis, a Tenured Professor, leads the Smart Agri Tech Research Lab and the Adaptive Signal Processing Lab at SINES, NUST. His work focuses on developing innovative, AI-driven smart agriculture technologies, including hardware and software solutions for precision farming, crop monitoring, yield optimization, and efficient resource management. The lab also specializes in real-time video analytics for agricultural and industrial applications, enhancing monitoring and decision-making processes.

Additionally, he works on predictive maintenance, energy monitoring, and Smart Home Solutions involving IoT and ML. These efforts integrate cutting-edge technologies to address critical challenges in agriculture, sustainable energy, and automation.

Master Capabilities of lab:

• Development and integration of advanced sensor technologies for diverse applications.
• Expertise in designing and implementing sensor-based solutions for monitoring, automation, and control systems.
• Prototyping and testing of sensor-driven platforms for industrial and research purposes.

• End-to-end IoT solutions, from device connectivity to cloud-based management.
• Development of IoT platforms for real-time data collection, analysis, and control.

• Integration of AI capabilities into embedded systems for intelligent decision-making at the edge.
• Deployment of machine learning models optimized for low-power and resource-constrained environments.
• Specialized in creating real-time AI solutions for robotics, automation, and smart devices.

• Expertise in hardware-software co-design for embedded systems across various industries.
• Support for full lifecycle development, including prototyping, testing, and deployment.

• Advanced video analytics solutions leveraging AI and deep learning techniques.
• Development of systems for object detection, tracking, and recognition in real-time.

• Scalable AI models for deployment across cloud, edge, and hybrid environments.

Lab Equipment /Resources:

•          PCB engraving CNC Machine
•          3D Printer
•          PCB Soldering Station
•          IoT Devices
•          Agri Robot
•          Power Supplies
•          Function Generator
•          Oscilloscope
•          Embedded Edge Devices
•          GPUs

Full time Human Resource:

•          03x Research Assistants
•          5x PhDs and 12+ MS (under supervision)
•          2 FYP Projects

Projects undertaken:

1. Low-Cost Seamless Facial Recognition Technology Development Using CCTV Cameras at RIC Building, NUST (2024-2025) – Upcoming – Funded by NUST (PKR 0.5 Million).
2. A Real-Time, Multi-Camera Automatic Number Plate Recognition System Design and Implementation at NUST Entry Points (2024) – Upcoming – Funded by NUST (PKR 0.3 Million).
3. Development of Tracking Portal for Restoration of Habitats (2022-2024) – Ongoing – Funded by Commercial Funding (PKR 1.0 Million).
4. Channel Estimation, Transceiver Design, and Network Optimization for 5G Mobile Communication Systems and Beyond Using Advanced Machine Learning Techniques (2022-2024) – Ongoing – Funded by NRPU-HEC (PKR 7 Million).
5. Multi-Sensor Data Fusion for Multiple Platforms (2019-2024) – Ongoing – Funded by Defense Organization (PKR 5 Million).

6. IoT-Based Industrial Load Monitoring and Management System (2019-2021) – Completed – Funded by TDF-HEC (PKR 15.48 Million).
7. CattleVitals: A Smart System for Silent Heat and Early Disease Detection in Buffaloes (2019-2022) – Completed – Funded by NRPU-HEC (PKR 2.22 Million).
8. Solar Powered Temperature and Relative Humidity Monitoring for Multipurpose Silo Bin (2017-2020) – Completed – Funded by Pakistan Agricultural Research Council (PARC) (PKR 7.22 Million).
9. Investigation of Flywheel Energy Storage System (FESS) for Replacement of Batteries for Smooth Transition from Grid to Other Sources (2018-2019) – Completed – Funded by USPCAS-E, NUST (PKR 0.76 Million).
10. HVACM&C: A Smart System for Advanced Control and Metering of HVAC (2018-2019) – Completed – Funded by USPCAS-E, NUST (PKR 0.72 Million).
11. SETD: A Smart System for Electricity Theft Detection (2018-2019) – Completed – Funded by USPCAS-E, NUST (PKR 0.68 Million).
12. Monitoring of Solar and Its Health Prediction (2019) – Completed – Funded by USPCAS-E, NUST (PKR 0.69 Million).
13. Energy Efficiency Kit (2019) – Completed – Funded by USPCAS-E, NUST (PKR 0.55 Million).

14. Random-Neighborhood-RAM: An FPGA-based Memory Architecture for Real-Time Random-Neighborhood Image and Video Processing Algorithms (2017-2018) – Completed – Funded by SGRP-HEC (PKR 0.445 Million).
15. iDOC: A Portable, Cost-Effective Diagnostic Screening Device for Early Dengue Fever Detection (2016-2018) – Completed – Funded by Pakistan Science Foundation (PKR 2.88 Million).
16. Design of Acoustic Target Finding System for Moving Platform (2015-2017) – Completed – Funded by NESCOM (PKR 0.1 Million).
17. Backend Design and Implementation of Ultrasonic Thickness Measurement Gauge (2014-2015) – Completed – Funded by SciFlair Pvt. Ltd (PKR 0.732 Million).
18. Wideband Spectrum Monitoring Using Automatic Modulation Classification (2012-2013) – Completed – Funded by King Saud University KSA (PKR 0.9 Million). [Redundant: Similar project with identical funding in the list above]
19. Reliable Collaborative Spectrum Sensing Approach Using SNR and Energy of Multiple Receivers (2012-2013) – Completed – Funded by King Saud University KSA (PKR 0.9 Million). [Redundant: Similar project with identical funding in the list above]
20. Design and Development of High-Speed Reconfigurable Architecture for Secure Data Transmission on FPGAs (2010-2011) – Completed – Funded by NUST Seed Money (PKR 1.412 Million).