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This paper focuses on a Natural Language Processing (NLP) system and Image Recognition using python and Raspberry Pi. NLP Engines are widely used in various tech domains such as surveillance, defense, advanced medical diagnosis, virtual assistant and machine learning. Open CV based image processing algorithm is applied for image recognition, facial comparison, pattern recognition, security system, object detection and deep learning. In this proposed system to implement intelligent QAS system, NLP and Image processing are integrated.

The presented article represents the rudimentary-shaped effective 1 × 2 MIMO antenna structure. The five variation types in the ground region shape are analyzed. The structure's total dimensions are 40 × 36 × 1.6 mm 3 . For efficiently manufacturing, the low-profile substrate FR4 is employed, and the reflectance response of a simulated and modelled design is compared. The placement of two T-shaped slits in the ground area aids in achieving a wider bandwidth, multiband response, excellent Gain, and directivity. Overall, the PW:4 has a minimum reflectance coefficient of −34.54 dB, a broad bandwidth of 3.38 GHz, a peak gain of 13.02 dB, maximum narrow band isolation of 62 dB, and a maximum normalized directivity of 156°. The Envelop Correlation Coefficient, Channel Capacity Loss, Total Active Reflection Coefficient, and Diversity Gain for MIMO design are also examined. These findings indicate the provided design's behavior as per the standard requirements.