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The development of sensor technologies in recent years makes it possible to acquire real-time states of building environment and its systems with a major trend towards big data and wireless data transmission. How to use these vast real-time data sets to achieve a safer, more comfortable and energy efficient building becomes a major challenge for building engineering. This paper investigates one of the possibilities of using the real-time data for the prediction of future fire development states. Beyond simply reflecting the real-time states of a system, the sensing data will be able to forecast a highly dynamic problem of building fire growth and smoke dispersion inside building environment. This paper presents the forecasting method based an ensemble Kalman filter (EnKF) to predict building fire smoke temperature and smoke layer height at the real time. Detailed formulations of the zonal fire smoke models and the EnKF model are presented. The proposed real-time forecasting method is demonstrated and validated by a 1:5 scaled compartment fire experiment. The results indicate that real-time forecasting of building fires is achievable while the accuracy is noticeable which can be applied to assist emergency evacuation and firefighting.

A CMOS analog and audio front-end circuit includes an enhanced analog-to-digital converter (ADC) that achieves a desired signal-to-noise-and-distortion (SNDR) and an analog-front-end transmit (TX) digital-to-analog converter (DAC). The enhanced ADC includes an improved single Op-Amp resonator coupled to a feed-forward loop and can substantially reduce signal transfer function (STF) peaking of the enhanced ADC. The CMOS analog and audio front-end circuit is integrated with a baseband processor.

Data assimilation (DA) is a technique to combine numerical predictions and experimental measurements, which has been commonly used by the community of numerical weather forecasting but is relatively new to the field of indoor environment. Among all data assimilation methods, Ensemble Kalman Filter (EnKF) is especially suitable to solve large-scale nonlinear problems due to its low computation requirement. In this paper, two new applications of EnKF to forecasting indoor environment are presented. The first study is to forecast the contaminant transport in a residential house based on a multi-room tracer gas decay experiment. The forecast model avoids calculating source term in the given problem by rapid updating model states with EnKF while still providing significant forecast lead time. The second study is to predict the fire smoke dispersion in a multi-room compartment fire without giving actual heat release rates (HRRs) as model inputs. Compared to conventional deterministic models, the EnKF models improve the predictions significantly.

This paper presents the design and characterization of the first RF MEMS phase shifter to be monolithically integrated with conventional CMOS using maskless post-CMOS etching. The phase shifter consists of a micromachined transmission line periodically loaded with 4-bit MEMS digital capacitors, which are controlled using a combination of vertical electrothermal and lateral electrostatic actuation. MIM capacitors are embedded in the transmission line in series with MEMS capacitors to trade tuning ratio for increased capacitor Q. Measured results of the phase shifter at 32 GHz show an average insertion loss of 2.9 dB and a maximum phase shift of 337.57#x00B0; in 16 steps.

A monolithically integrated differential class E power amplifier capable of dynamically switching between 3.4 GHz and 4.3 GHz operation has been designed and fabricated in a 0.35 µm BiCMOS process; this power amplifier also includes an integrated CMOS-MEMS variable capacitor enabled LC balun for differential to single-ended conversion. The power amplifier achieves a maximum output power of 19.1 dBm and a maximum power added efficiency of 15.1% with a supply voltage of 3.3 V.

A low-power frequency-reconfigurable narrowband LNA and PA have been designed using tunable RF-MEMS passives in a 0.35 µm BiCMOS process. The LNA's operating frequency varies from 2.7 GHz to 3.1 GHz and the PA's operating frequency varies from 2.7 GHz to 3.2 GHz (using the current 2.5:1 varactor tuning range; next generation varactors have 6.9:1 tuning range). With only 2.5 mW of power the LNA attains (S 21 , NF) of (7.7 dB, 4.2 dB) at 2.7 GHz and (10.2 dB, 4.8 dB) at 3.1 GHz. The PA delivers 10.1–13.7 dBm of power and has a PAE of 7.5–17% depending on the frequency.

The design and characterization of a CMOS-MEMS variable capacitor is presented. Measured results demonstrate a tuning ratio of 6.9:1, a quality factor of 28 at 3 GHz, and a self-resonant frequency of 11 GHz, with sub-50 fF parasitic capacitance. Simulations of two frequency-reconfigurable circuits, a low-noise amplifier and a power amplifier, show the importance of low parasitic capacitance for practical reconfigurable front-end designs.