Digital system algorithms such as FFT algorithms, convolution, image processing algorithm, etc. deploy Multiply and Accumulate (MAC) unit as an evaluative component. The efficiency of a MAC typically relies on the speed of operation, power dissipation, and chip area along with the complexity level of the circuit. In this research paper, a power-delay-efficient signed-floating-point MAC (SFMAC) is proposed using Universal Compressor based Multiplier (UCM). Instead of having a complex design architecture, a simple multiplexer-based circuit is used to achieve a signed-floating output. The 8£8 SFMAC can take 8-bit mantissa and 3-bit exponent and therefore, the input to the SFMAC can be in the range of –(7.96875)₁₀ to +(7.96875)₁₀. The design and implementation of the proposed architecture is executed on the Cadence Spectre tool in GPDK 90 nm and TSMC 130 nm CMOS, which proves as power and delay efficient.

Background: a humidity sensor is used to sense and measure the relative humidity of air. A new composite system has been fabricated using environmental pollutants such as carbon black and low-cost zinc oxide, and it acts as a humidity sensor. Residual life of the sensor is calculated and an expert system is modelled. For properties and nature confirmation, characterization is performed, and a sensing material is fabricated. Methodology: characterization is performed on the fabricated material. Complex impedance spectroscopy (CIS), Fourier transform infrared spectroscopy (FTIR), X-ray diffraction (XRD) and scanning electron microscopy (SEM) are all used to confirm the surface roughness, its composite nature as well as the morphology of the composite. The residual lifetime of the fabricated humidity sensor is calculated by means of accelerated life testing. An intelligent model is designed using artificial intelligence techniques, including the artificial neural network (ANN), fuzzy inference system (FIS) and adaptive neuro-fuzzy inference system (ANFIS). Results: maximum conductivity obtained is 6.4×10⁻³ S/cm when zinc oxide is doped with 80% of carbon black. Conclusion: the solid composite obtained possesses good humidity-sensing capability in the range of 30–95%. ANFIS exhibits the maximum prediction accuracy, with an error rate of just 1.1%.