Profiling and minimizing the energy consumption of resource-constrained devices is an essential step towards employing IoT in various application domains. Due to the large size and high cost of commercial energy measurement platforms, alternative solutions have been proposed by the research community. However, the three main shortcomings of existing tools are complexity, limited measurement range, and low accuracy. Specifically, these tools are not suitable for the energy measurement of new IoT devices such as those supporting the 802.11 technology. In this paper we propose EMPIOT, an accurate, low-cost, easy to build, and flexible power measurement platform. We present the hardware and software components of this platform and study the effect of various design parameters on accuracy and overhead. In particular, we analyze the effects of driver, bus speed, input voltage, and buffering mechanism on sampling rate, measurement accuracy and processing demand. These extensive experimental studies enable us to configure the system in order to achieve its highest performance. We also propose a novel calibration technique and report the calibration parameters under various settings. Using five different IoT devices performing four types of workloads, we evaluate the performance of EMPIOT against the ground truth obtained from a high-accuracy industrial-grade power measurement tool. Our results show that, for very low-power devices that utilize 802.15.4 wireless standard, the measurement error is less than 3.5%. In addition, for 802.11based devices that generate short and high power spikes, the error is less than 2.5%.
E-selectin, an adhesion molecule, is detectable in the blood. Serum levels of E-selectin can be a prognostic indicator for various malignancies. We developed a microplate enzyme-linked immunosorbent assay (ELISA) for the detection of circulating E-selectin by coating the microwell with monoclonal anti-E-selectin. We incubated the specimen and the biotinylated detecting antibody simultaneously, and used HPR-conjugated streptavidin to generate a signal for quantification. The assay has a sensitivity of 3.8 ng/mL, and the coefficients of variation (CVs) for both within-day and day-to-day precision were all <10%. Our in-house-made kit also compared well with a commercial kit from R&D Systems (r=0.95, slope=0.94). Using our kit we determined a normal reference value for Chinese individuals of different ages (30-80 years). We found no significant difference between females and males; however, age appeared to have an impact on the normal E-selectin value. We found that normal individuals over 60 years old had higher levels of circulating E-selectin (65.8+/-19.5 ng/mL, N=111) compared to those under 60 years old (59.5+/-18.1 ng/mL; P=0.002). Our kit appears to have sufficient sensitivity for detecting elevated circulating E-selectin in various carcinomas. We believe that with the established normal reference value, our in-house-developed ELISA kit is well suited for routine clinical laboratory use.
Calibration is an important step towards building reliable IoT systems. For example, accurate sensor reading requires ADC calibration, and power monitoring chips must be calibrated before being used for measuring the energy consumption of IoT devices. In this paper, we present ProCal, a low-cost, accurate, and scalable power calibration tool. ProCal is a programmable platform which provides dynamic voltage and current output for calibration. The basic idea is to use a digital potentiometer connected to a parallel resistor network controlled through digital switches. The resistance and output frequency of ProCal is controlled by a software communicating with the board through the SPI interface. Our design provides a simple synchronization mechanism which prevents the need for accurate time synchronization. We present mathematical modeling and validation of the tool by incorporating the concept of Fibonacci sequence. Our extensive experimental studies show that this tool can significantly improve measurement accuracy. For example, for ATMega , the ADC error reduces from . % to . %. ProCal not only costs less than % of the current commercial solutions, it is also highly accurate by being able to provide extensive range of current and voltage values.
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