We present in this paper a method and apparatus for nonintrusive measurement of active energy in low-voltage ac installations. In the proposed method, the active power is calculated from the voltage and current waveforms, and the phase shift between them. No voltage amplitude measurement is required since the nominal voltage of the ac installation is considered as the actual voltage. This approach bypasses the main disadvantage of capacitive ac voltage probing: low accuracy in amplitude measurements due to variations on the sensor coupling capacitance. The energy meter that implements the technique is composed of a commercial nonintrusive current sensor (clamp-on current transformer) and a contactless capacitive voltage sensor-designed to measure the voltage phase and waveform. The voltage sensor includes a shield to isolate it from external electric fields, making the energy meter suitable for applications in polyphase systems. The developed energy meter does not require on-site calibration, galvanic contact to the phase conductors, neither electrical circuit opening, allowing for quick, safe, and easy installation on overhead service drop line. Due to these characteristics, it can be used by electricity distribution companies in the preinspection of consumer units suspected of fraud. Experimental results proved that the developed energy meter is insensitive to the characteristics of cables (width and insulation), external electrical fields, as well as to the voltage sensor capacitance variations. The error of the active energy measurement under real condition in a two-phase installation was 1%.

We present the design and fabrication of a reconfigurable smart-sensor for measuring moisture content (MC) and temperature in grains stored in silos, using a capacitance fringing field interdigitated sensor and using a resistance temperature detector (RTD), both implemented on a single conventional printed circuit board. The sensor was tested in laboratory, using corn kernels with percent MC in the range of MC $= 8\%$ to MC $= 32 \%$ and, using a simple relaxation oscillator and a frequency-to-voltage converter, we measured a capacitance variation of $\Delta C = 4.99$ pf, with a sensitivity $S = 0.21 \, \rm {pF}/\%$ MC. The RTD sensor, which uses the copper resistance of the PCB tracks, was characterized in the 10 $^\circ \text{C}$ – $50~^\circ \text{C}$ temperature range and the measured results presented a very linear behavior ( $R^{2} = 0.99888$ ) when compared to the measured temperature values using a commercial sensor (LM135). A modified bridge circuit was developed, where a linear behavior of the differential output was obtained. The developed configuration allowed for the independent adjustment of both the offset and the gain in the output voltage $V_{\text {out}}$ of the bridge. The bridge signal processing circuit was calibrated using an endpoint method, and the measured points between the calibration points presented a maximum endpoint nonlinearity error of $|E_{\text {nl}}| =\,\,0.64\,\,^\circ \text{C}$ .

We propose an autonomous energy wireless sensor node for monitoring rotation machines condition. The thermal energy dissipated during normal operation of the motor can be harvested to power an ultra low power wireless sensor. The harvested energy is stored in supercapacitors instead of lithium-ion battery, providing an extended life for the energy storage element and being able to handle high energy radio transmission pulses. The proposed system may be used on early fault diagnosis through pervasive data collection of machines condition. The collected data can provide a maintenance schedule programming with low impact in plant operation, reducing unexpected production stop due motors failures.

A low-cost signal processing circuit developed to measure and drive a heat dissipation soil matric potential sensor based on a single thermosensitive resistor is demonstrated. The ${\mathrm{SnSe}}_2$ has a high thermal coefficient, from $-2.4\Omega {/}^{°}$C in the 20 to 25 ${}^{°}$C to $-1.07\Omega {/}^{°}$C in the 20 to 25 ${}^{°}$C. The ${\mathrm{SnSe}}_2$ thermosensitive resistor is encapsulated with a porous gypsum block and is used as both the heating and temperature sensing element. To control the power dissipated on the thermosensitive resistor and keep it constant during the heat pulse, a mixed analogue/digital circuit is used. The developed control circuit is able to maintain the dissipated power at $327.98\pm 0.3\%$ mW when the resistor changes from $94.96\Omega$ to $86.23\Omega$. When the gravimetric water content of the porous block changes from dry to saturated (${\theta }_w=36.7\%$), we measured a variation of $4.77\Omega$ in the thermosensitive resistor, which results in an end-point sensitivity of 130 m$\Omega$/%. The developed system can easily meet the standard requirement of measuring the gravimetric soil water content with a resolution of approximately $\Delta {\theta }_w=1\%$, since the resistance is measured with a resolution of approximately μ$31\mathsf{\mu }\Omega$, three orders of magnitude smaller than the sensitivity.

We present in this paper a simple and low-cost Power Line Communication (PLC) modem for Internet of Things (IoT) applications. The proposed modem implements a simple on-off-keying (OOK) modulation/demodulation with only discrete electronic components, not requiring complex ICs, such as processing units. It uses the ground and neutral wires as a channel communication, eliminating the need for complex isolation circuitry. To improve its robustness to noise, the developed PLC modem includes an automatic receiver gain adjustment and a transmitter sweep carrier frequency algorithm. Laboratory tests show that the developed PLC modem is capable of transmitting data at 9,600 bps with no errors if the noise spectral density in the power line is below 111 nVRMS2/Hz in the bandwidth of 150 kHz to 500 kHz. The system was also evaluated in a residential power network, where it presented a bit error rate below 1.21%. Due to its low cost, the developed PLC modem is suitable for low data rate IoT applications such as energy consumption monitoring, appliance monitoring and control, environmental monitoring (temperature, humidity, luminosity), security monitoring (presence sensors), etc.