coverage area side view takes 3 values which are the coverage distance above, beneath and in front of the sensor
coverage area top view takes 3 dimensions wich are the distance to the left, right and in front of the sensor.
The method used by the device to transfer the data it measures
The formats and encoding of device produced or measured data
Different mathematical formulas that can be used to estimation or composition of measurements Formulas used for composition have a structure that should be used in the java code to be able to parse the formula string into mathematical formula
the industrial model contains the information/production specific details of the sensor compoment used in the device model
this is the information devices give me, all i know is the type of the sensor used not an industrial model. maybe i should skip that one?
a camera is an example of a device that has two sensors in it: the image sensor and the microphone. a camera can also have a motion sensor
Measurement = x + Normal Distribution(Mean, Variance)
Measurement with Additive Gaussian Noise 1D Formula
All Weather Inc. 1165 National Drive Sacramento, CA 95834
Cisco WVC2300 Wireless-G Business Internet Video Camera with Two-way audio
i don t know if it is periodic or event based..maybe it is both?
logically it should be push but i m not sure? to recheck in general about cameras
Continuous Normal Distribution Mean Formula
Continuous Uniform Distribution Probability Density Function Formula
if a<=x<=b PDF(x) = 1/(b-a) else PDF(x) = 0
Continuous Distribution Variance Formula
Discrete Distribution Total Number of Values
Discrete Uniform Distribution Mean Formula
Discrete Uniform Distribution Probability Mass Function Formula
if a<=x<=b PMF(x, Discrete Distribution Total Number of Variables) = 1/ Discrete Distribution Total Number of Variables else 0
Discrete Uniform Distribution Variance Formula
Exponential Distribution Probability Density Function Formula
if x>0 PDF(x, Rate) = Rate* exp(-Rate*x) else PDF(x, Rate) = 0
Exponential Distribution Variance Formula
MZT EKA D.O.O Pero Nakov Street bb 1000, Skopje Macedonia
IPP15-1L Decora Manual On Occupancy Sensor
Normal Distribution Probability Density Function Formula
PDF(x) = 1/RTSQRT[2*Pi*SQRT(Normal Distribution Variance)] * exp[(x- Normal Distribution Mean)/2* Normal Distribution Variance)]
P(Observation Sequence| Hidden Markov Model)
Oceanside Photo & Telescope 918 Mission Avenue Oceanside, CA 92054
Mean = Expected Number of Value Occurences
PMF(x = Exact Number of Occurences, Exact Number of Occurences) = [POWER(Expected Number of Occurences, Exact Number of Value Occurences) * exp (- Expected Number of Occurences)] / FACT(Exact Number of Occurences)
Poisson Distribution Probability Mass Function
Var = Expected Number of Value Occurences
Pois(Expected Number of Value Occurences)
again not sure what sampling type is. logically it should be periodic? although i think it should be both
TECMES Instrumentos Especiales S.R.L. Neuquén 1123-Buenos Aires, Argentina
Thermokon SensorTtechnik GmbH - Aarstrasse 6 - 35756 Mittenaar
windchill = (10* ws toThePower 0.5-ws+10.5)*(33-Ta)