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IHIL

Located in room 104, IHIL lab  section is home to advanced NIR (Near Infrared spectroscopy) and NIR-HSI (Near Infrared Hyperspectral Imaging) devices renowned for their extensive wavelength range and versatile applications. NIR spectroscopy analyzes materials based on their absorption of near-infrared light, while NIR-HSI provides detailed spectral and spatial data.

These instruments enable comprehensive recording and analysis across a wide spectrum, offering unparalleled insights into material composition, characteristics, and behaviors. Our lab provides academics, scientists, and business professionals with essential tools to reveal concealed data, fostering informed decisions with unparalleled precision.

Portable IQ Camera

The Specim IQ is a hyperspectral imaging (HSI) camera that is known for its advanced capabilities and applications in various fields such as agriculture and  food analysis.

Typically covers a spectral range from 400 nm to 1000 nm, which includes the visible to near-infrared spectrum.

Provides high spatial and spectral resolution, allowing for detailed analysis of the spectral characteristics of the sample.

Compatible with various software tools for advanced data analysis and interpretation. It often comes with proprietary software for managing and analyzing hyperspectral data.

Vegetation Research, Food Analysis, Health Sector

Resonon Hyperspectral Imaging Equipment

Resonon provides advanced hyperspectral imaging (HSI) equipment designed for detailed spectral and spatial analysis. Their Pika series cameras are versatile and used across various scientific and industrial fields.

Pika L Camera

  • Spectral Range: 400 nm – 1000 nm (Visible to Near-Infrared)
  • Description: The Pika L camera captures high-resolution hyperspectral data in the visible to near-infrared range. It is ideal for applications requiring detailed analysis of the visible spectrum along with the near-infrared.

Use: Crop health monitoring, food quality control, mineral identification, and environmental monitoring.

Pika NIR Camera

  • Spectral Range: 900 nm – 1700 nm (Near-Infrared)
  • Description: The Pika NIR camera captures hyperspectral data in the near-infrared range, providing detailed information that is beyond the visible spectrum.

Use: Industrial inspection, material identification, biomedical applications, and water quality analysis.

Vegetation Research, Food Analysis, Health Sector

NIR INSTALAB 700

The Instalab® 700 (IL700) is a self-contained optical reflectance instrument designed for the
rapid and precise measurement of constituent concentrations such as moisture, protein,
oil, starch, fiber, and ash in various commodities prevalent in the grain, feed, and food
industries.

1100 nm to 2500 nm (Near-Infrared)

This non-NTEP grain analyzer stands out by its ability to detect protein and moisture in whole
grain wheat, bypassing the conventional process of grinding and preparing samples.

TANGO FT-NIR Spectrometer

The TANGO FT-NIR spectrometer offers a wide spectral range and high-resolution capabilities. It is designed to provide quick and reliable results with minimal sample preparation, making it ideal for routine analysis and quality control.

4000 cm⁻¹ to 12,500 cm⁻¹ (Near-Infrared)/ 800 nm – 2500 nm (Near-Infrared)

Pharmaceutical industry (e.g., raw material identification, quality control), food and beverage industry (e.g., ingredient analysis, quality assessment), chemical industry (e.g., process monitoring, composition analysis), and agricultural applications (e.g., feed and crop analysis).

Khaliduzzaman

His groundbreaking work focuses on the transformation of the egg industry through the integration of advanced technologies. By utilizing non-destructive optical sensing, IoT, AI, big data, and cloud computing, he aims to develop smart systems for egg production, quality inspection, and grading. His research highlights the potential of these innovations to enhance automation, biosecurity, and animal welfare. A significant part of his work involves applying various CNN and transfer learning models for nondestructive chicken egg fertility detection, demonstrating their high accuracy and potential for industry-wide implementation

1.  Ahmed, M. W., Hossainy, S. J., Khaliduzzaman, A., Emmert, J. L., & Kamruzzaman, M. (2023). Non-destructive optical sensing technologies for advancing the egg industry toward industry 4.0: A review. Comprehensive Reviews in Food Science and Food Safety, 22, 4378–4403. Link to DOI