This paper presents the design of a low-voltage ultralow-power relaxation oscillator without external components. The application field for this oscillator is the clock generation of low-power wake-up functions for battery-operated systems. A detailed analysis of the oscillator, including the temperature performance, is derived and verified with experimental results. The oscillator operates at a typical frequency of 3.3 kHz and consumes 11 nW from a 1-V supply at room temperature, and a temperature drift of less than 500 ppm/°C is achieved over the temperature range of -20°C to 80°C. An efficient design implementation has resulted in a cell area of 0.1 mm2 in a standard 0.35- μm digital CMOS technology.

Analysis and Design of an Ultralow-Power CMOS Relaxation Oscillator

Construction of wireless sensor for harsh environment operation

Wireless sensor networks are nowadays a reality. However, a wireless node must be a truly autonomous system, i.e., it must embed its own power source, which is generally a battery pack. For this reason, it is of main concern to limit every source of wasted power. In particular, nodes exploit low-duty-cycle strategies to increase their life, spending most of their time in low-power mode, turning off all devices within the system except a wake-up oscillator. However, this way, some time must be spent waiting for the circuitry settling time, particularly if a high-accuracy measurement is required. In this paper, an efficient implementation of a filtering algorithm that is able to reduce this time is discussed. It is based on a hybrid combination of a median and a mean filter, joining the advantages of both linear and nonlinear filtering. A well-tailored implementation has experimentally been tested and discussed. Two wireless prototypes have been realized to test the proposed filter performance for temperature and humidity measurements. The experimental results permit comparing the implemented filters in terms of computational time, power consumption, and the performance of noise filtering. For both sensors, the new filtering strategy resulted to be more efficient in terms of noise removal and consumption than traditional algorithms. In particular, in the case of slow sensors such as a humidity one, delays are dictated by the sensor itself, and computational time can be neglected, while for fast sensors such as a temperature one, the proposed schema greatly improves the system update rate.

Efficient Sensor Signal Filtering for Autonomous Wireless Nodes

Analysis and Design of an Ultralow-Power CMOS

Cyclist Safety Device based on Spectral Audio Processing for Approaching Vehicles Detection

Wireless Sensor Networks arenowadays a reality. However, awireless nodemustbeatruly autonomous system, i.e. it mustembedits ownpowersource, generally abattery pack. Forthis reason, itisofmainconcern tolimit every source ofwastedpower. Inparticular, nodesexploit lowduty-cycle strategies toincrease their life, spending mostoftheir timeinlowpowermode, turning off alldevices within thesystem except awakeup oscillator. However, inthis waysometimemustbespent waiting forcircuitries settling time, especially ifahighaccuracy measurement isrequired. Inthis paperanefficient implementation ofafiltering algorithm thatis abletoreduce thistimeisdiscussed. Itisbasedona hybrid combination ofmedian andmeanfilter, joining advantages ofboth linear andnon-linear filtering. A welltailored implementation has beenexperimentally tested anddiscussed. fields, ashomeautomation, environmental monitoring and process control (1).Wireless transceiver costisquickly decreasing andemerging technologies (e.g. IEEE802.15.4) allow apowerreduction inorder toobtain autonomous and mobile sensors (2). Nowadays batteries arethemostcommon waytorealize autonomous sensors andseveral research activities concern withanefficient useofbatteries (3). Onthe other hand, manymethods ofpowerharvesting (solar cell, electromagnetic fields,piezoelectric generators, thermopiles...) aregrowing (4); theycanbeusedtorecharge batteries ortoreplace batteries. Inbothcaseslow-power techniques mustbeadopted tosavethesmall amountof available power. Inmostofapplications, thewireless sensor periodically wakesup,measures theinteresting quantity and, ifnecessary, transmits information. Inthecaseofhumidity or temperature sensor, information transmission rarely occurs, because humidity ortemperature variation isveryslow. In mostcases, themeasure isrepeated every second while data transmission takes place less thanonetimeevery minute. For thisreason, inorder tosavefurther power,thesensing element andtheinterface circuits arepowered just before the measure andthenthey areturned offassoonasthemeasure isover. Bothsensing element andelectronic interface circuits require a certain timetofurnish a stable andaccurate measurement. Inthefollowing, atemperature/humidity sensor istaken intoaccount, buttheproposed approach canbeusedwith othertypeofsensors. Typical temperature orhumidity sensors usedinlow-cost applications areresistive or capacitive sensors. Inthefirst case, thesensor canbeinserted inavoltage divider andtheoutput voltage isacquired by meansofananalog-to-digital converter. Inthesecond case, thesensor isusedinanoscillating circuit, e.g. based onthe 555multivibrator device, andamicrocontroller estimate the output signal period byexploiting itstiming unit. Inboth cases, thecircuits mustbeoperative forashort time, sothat thepowerconsumption could belimited. Ontheother hand, theuseoffilters ishighly advisable, inorder toimprove the signal-to-noise ratio. However, low-pass filters applied to signals andpowersupply cause alongmeasure settling time. Asaconsequence, anenlargement oftheoperative timeof thesensor, microcontroller andinterface circuits isproduced whichdetermines anincrement ofthepowerconsumption. A simple andlargely employed solution iswaiting fora fixed timetoperform themeasure after thepowersupply has beenapplied tothesensors andthecircuits. Thisfixed time value isestablished intheproject stage bymeansofa-priori considerations about thesystem. However, this solution is neither flexible norefficient, because thetimevalueis usually oversized. Thisisduetothecircuit output settling timewhichisnotusually specified inthecomponent data sheetsand,furthermore, itstrictly dependson the temperature, powersupply andloadconditions. Inaddition, evenforthesamecomponent, itcanvaryamongdifferent manufacturers, especially ifthecomponent isnotspecifically developed forlowpowerapplications. Forthese reasons, usually theoutput signal fromthe sensor iscontinuously measured until itreaches a stable value. Thisoperation isnotalways simple, because ofthe noise overlapped tothesignal, whichmakesthetimetogeta stable value longer. Fromadifferent point ofview, this isa typical pattern recognition problem, madeup ofa pre- processing, feature extraction anddetection phase. Feature extraction canbeperformed bymeansofedgedetection (analyzing thegradient ofthemonitored signal), while forthe detection asimple threshold rule canbeused. However, these steps workswellonlyinabsence ofnoise, thatmustbe eliminated bythepre-processing stage. Inconclusion, theuse ofa suitable filter ishighly recommended; itshould be effective towards different noise typologies, butitdoesnot havetoincrease toomuchthemeasure time. Inaddition, it should befast andeasytoimplement inorder tonotincrease microcontroller cost. Incaseofsignal affected byGaussian noiseoverlapped withimpulsive noise, asithappens for

Sensor Signal Processing forAutonomous Wireless Sensors

Popular Tasks used by Researchers

How can I help with your research?

Get more enhanced response by uploading the PDFs you want me to reference.

No relevant PDFs in your library

SciSpace is the AI research assistant for academics. Run systematic literature reviews on 280M+ papers, and write papers with cited sources. Trusted by 1M+ students, PhDs & researchers.

SciSpace | AI for Research

We encountered an error while loading the panel. Please try refreshing the page.

Something went wrong

Analyze PDFs

Code & Manuscripts

Funding & Grants

Literature & Patents

Medical & Clinical Data

Systematic Review

Visualize & Present

Web & Data

Build a Google Scholar-like website for your research.

Build a website

Create charts and images for your research

Create a Chart

Write a paper for submission to a journal

Draft a manuscript

Patent Search

Design eye-catching scientific posters in minutes.

Scientific Poster Generation

Systematic Literature Review

Anyone with the link can view this chat. You can switch it back to private anytime.

One task is running at the moment. Your messages will be shown right after.

Drag and drop or click here to browse

Loved by <highlight>1 million+</highlight> researchers

Extract a list of specific topics and their sources from unstructured text

Topics

Compare and analyze relevant papers that matches with your search

Papers

Get insights from PDFs and bookmarked papers from your library

My library

Recent searches

Try searching for:

Catch AI-generated content in scholarly and non-scholarly content

{ai} Detector

Ai Writer

Get PDF Summaries, highlighted text explanations 

Chat with PDF

Effortlessly create in-text citations and bibliographies in APA and 2,500 other formats

Citation generator

Get explanations, summaries, and answers on academic papers

Ease up your research workflow with {scispace}'s cohort of exciting AI tools

Elevate your academic writing skills and convey your ideas the way you want

Paraphraser

Explore our range of reading and writing tools

Your file is being prepared and should be ready in a few minutes. If it's a large file, it might take a bit longer. You can close this window, and we'll email you the file when it's done.

You have reached a maximum limit of <strong>{limit}</strong> columns in the table. Remove at least <strong>1</strong> column to add or create another one.

A. Taronj

Author Tools

Chat about Author

Papers

Sensor Signal Processing forAutonomous Wireless Sensors