A Universal Intelligent System-on-Chip Based Sensor Interface

Mattoli, Virgilio; Mondini, Alessio; Mazzolai, Barbara; Ferri, Gabriele; Dario, Paolo

doi:10.3390/s100807716

Cited by 20 publications

(11 citation statements)

References 25 publications

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“…Besides functionality extension, the efficiency of intelligent sensors has also been addressed. Examples are the extension of self-powered wireless sensor nodes' battery lifetime using artificial learning methodologies [12], neural network based auto-calibration procedures [13], or the development of a system-on-chip device to ease the implementation and standardisation of intelligent sensors [14]. …”

Section: Introductionmentioning

confidence: 99%

A Neural Network Based Intelligent Predictive Sensor for Cloudiness, Solar Radiation and Air Temperature

Ferreira

Gomes

Martins

et al. 2012

Sensors

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Accurate measurements of global solar radiation and atmospheric temperature, as well as the availability of the predictions of their evolution over time, are important for different areas of applications, such as agriculture, renewable energy and energy management, or thermal comfort in buildings. For this reason, an intelligent, light-weight and portable sensor was developed, using artificial neural network models as the time-series predictor mechanisms. These have been identified with the aid of a procedure based on the multi-objective genetic algorithm. As cloudiness is the most significant factor affecting the solar radiation reaching a particular location on the Earth surface, it has great impact on the performance of predictive solar radiation models for that location. This work also represents one step towards the improvement of such models by using ground-to-sky hemispherical colour digital images as a means to estimate cloudiness by the fraction of visible sky corresponding to clouds and to clear sky. The implementation of predictive models in the prototype has been validated and the system is able to function reliably, providing measurements and four-hour forecasts of cloudiness, solar radiation and air temperature.

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Section: Introductionmentioning

confidence: 99%

A Neural Network Based Intelligent Predictive Sensor for Cloudiness, Solar Radiation and Air Temperature

Ferreira

Gomes

Martins

et al. 2012

Sensors

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“…T HE design of reliable, low-maintenance, and real-time portable sensing systems is becoming critical to fully benefit from present-day technologies in the environmental, medical, and industrial fields [1]. One of the problems encountered in low-voltage power-efficient sensors is the low output signal level to be detected.…”

Section: Introductionmentioning

confidence: 99%

CMOS Low-Power Lock-In Amplifiers With Signal Rectification in Current Domain

Maya-Hernandez

Sanz-Pascual

Calvo³

2015

IEEE Trans. Instrum. Meas.

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This paper presents the design and experimental characterization of two lock-in amplifier (LIA) prototypes integrated in a 0.18-µm CMOS process with a single supply voltage of 1.8 V. As opposed to previously reported integrated LIAs, synchronous rectification is performed in the current domain, providing key features such as low power (<420 µW) and reduced area (0.013 mm 2 ), with a dynamic reserve better than 35 dB and less than 5% relative error in the signal recovery. The principle of operation of each prototype is presented and their performance is compared with previous implementations, validating their suitability for low-cost portable applications.Index Terms-Analog integrated design, analog processing circuits, lock-in amplifiers (LIAs), low-voltage low-power, programmable circuits.

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“…Hence, the use of FPGA to implement sensor networks will be an efficient solution for a reliable on-chip sensor network packet transmission and retransmission scheme because logic and critical-path delays in FPGAs are minimal. Several methods to overcome these limitations include the use of feedback control system [5,6,[11][12][13][14].…”

Section: Introductionmentioning

confidence: 99%

FPGA-Based Design of an Intelligent On-Chip Sensor Network Monitoring and Control Using Dynamically Reconfigurable Autonomous Sensor Agents

Abba

Lee

2016

International Journal of Distributed Sensor Networks

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This paper proposes different low-level microarchitectural designs and frameworks for real-time monitoring and efficient control of on-chip sensor network for field programmable gate arrays (FPGAs). The main goals are to design low power, low-cost, and highly accurate monitoring and control mechanism using autonomous sensor agents and to dynamically reconfigure control of onchip sensor networks by FPGAs. By collecting dynamic and real-time monitoring parameters such as voltage and temperature, the system becomes self-aware and is able to improve the utilization of FPGA resources and power consumption. The FPGA synthesis, place and route, and implementation were performed for the proposed design. The results after synthesis and implementation show a significant low usage of FPGA logic resources and efficient power consumption of all on-chip sensor components compared with previous approaches. Furthermore, the experimental results from the FPGA-measured on-chip sensor readings show high precision and accuracy in the measured voltage and temperature. Setting the dynamic reconfiguration refresh time at 1000 ms produces highly accurate FPGA-measured on-chip sensor readings compared with those at 100 and 500 ms. The proposed design technique and framework will assist network engineers and system designers by providing flexible and efficient real-time monitoring and control design of large and complex on-chip sensor networks and remote-sensing applications.

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A Universal Intelligent System-on-Chip Based Sensor Interface

Cited by 20 publications

References 25 publications

A Neural Network Based Intelligent Predictive Sensor for Cloudiness, Solar Radiation and Air Temperature

A Neural Network Based Intelligent Predictive Sensor for Cloudiness, Solar Radiation and Air Temperature

CMOS Low-Power Lock-In Amplifiers With Signal Rectification in Current Domain

FPGA-Based Design of an Intelligent On-Chip Sensor Network Monitoring and Control Using Dynamically Reconfigurable Autonomous Sensor Agents

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