[R] Temperature Prediction Model

[Clint Bowman]

Aneeta,

If I understand the figure at
<http://db.csail.mit.edu/labdata/labdata.html> this problem deals 
with sensors in a lab that is probably isolated from outdoor 
temperature changes.

I assume the predictive model must detect when a "rampaging 800 
pound gorilla" messes with a sensor.  Do we also have to detect the 
pawing of a "micro-mouse" as well?

The collected data also seem to have other parameters which would 
be valuable--are you limited to just temperature?

Clint

-- 
Clint Bowman			INTERNET:	clint at ecy.wa.gov
Air Quality Modeler		INTERNET:	clint at math.utah.edu
Department of Ecology		VOICE:		(360) 407-6815
PO Box 47600			FAX:		(360) 407-7534
Olympia, WA 98504-7600

On Thu, 22 Oct 2009, Thomas Adams wrote:

> Aneeta,
>
> You will have to have a seasonal component built into your model, because the 
> seasonal variation does matter, particularly -where- you are geographically 
> (San Diego, Chicago, Denver, Miami are very different). Generally, there is a 
> sinusoidal daily temperature variation, but frontal passages and 
> thunderstorms, etc., can and will disrupt this nice pattern. You may have to 
> tie this into temperature predictions from a mesoscale numerical weather 
> prediction model. Otherwise, you will end up with lots of misses and false 
> alarms…
>
> Regards,
> Tom
>
> Aneeta wrote:
>>  The data that I use has been collected by a sensor network deployed by
>>  Intel.
>>  You may take a look at the network at the following website
>>  http://db.csail.mit.edu/labdata/labdata.html
>>
>>  The main goal of my project is to simulate a physical layer attack on a
>>  sensor network and to detect such an attack. In order to detect an attack
>>  I
>>  need to have a model that would define the normal behaviour. So the actual
>>  variation of temperature throughout the year is not very important out
>>  here.
>>  I have a set of data for a period of 7 days which is assumed to be the
>>  correct behaviour and I need to build a model upon that data. I may refine
>>  the model later on to take into account temperature variations throughout
>>  the year.
>>
>>  Yes I am trying to build a model that will predict the temperature just on
>>  the given time of the day so that I am able to compare it with the
>>  observed
>>  temperature and determine if there is any abnormality. Each node should
>>  have
>>  its own expectation model (i.e. there will be no correlation between the
>>  readings of the different nodes).
>> 
>>
>>  Steve Lianoglou-6 wrote:
>> 
>> >  Hi,
>> > 
>> >  On Oct 21, 2009, at 12:31 PM, Aneeta wrote:
>> > 
>> > 
>> > >  Greetings!
>> > > 
>> > >  As part of my research project I am using R to study temperature data
>> > >  collected by a network. Each node (observation point) records 
>> > >  temperature of
>> > >  its surroundings throughout the day and generates a dataset. Using the
>> > >  recorded datasets for the past 7 days I need to build a prediction 
>> > >  model for
>> > >  each node that would enable it to check the observed data against the
>> > >  predicted data. How can I derive an equation for temperature using the
>> > >  datasets?
>> > >  The following is a subset of one of the datasets:-
>> > > 
>> > >       Time              Temperature
>> > > 
>> > >  07:00:17.369668   17.509
>> > >  07:03:17.465725   17.509
>> > >  07:04:17.597071   17.509
>> > >  07:05:17.330544   17.509
>> > >  07:10:47.838123   17.5482
>> > >  07:14:16.680696   17.5874
>> > >  07:16:46.67457     17.5972
>> > >  07:29:16.887654   17.7442
>> > >  07:29:46.705759   17.754
>> > >  07:32:17.131713   17.7932
>> > >  07:35:47.113953   17.8324
>> > >  07:36:17.194981   17.8324
>> > >  07:37:17.227013   17.852
>> > >  07:38:17.809174   17.8618
>> > >  07:38:48.00011     17.852
>> > >  07:39:17.124362   17.8618
>> > >  07:41:17.130624   17.8912
>> > >  07:41:46.966421   17.901
>> > >  07:43:47.524823   17.95
>> > >  07:44:47.430977   17.95
>> > >  07:45:16.813396   17.95
>> > > 
>> >  I think you/we need much more information.
>> > 
>> >  Are you really trying to build a model that predicts the temperature 
>> >  just given the time of day?
>> > 
>> >  Given that you're in NY, I'd say 12pm in August sure feels much 
>> >  different than 12pm in February, no?
>> > 
>> >  Or are you trying to predict what one sensor readout would be at a 
>> >  particular time given readings from other sensors at the same time?
>> > 
>> >  Or ... ?
>> > 
>> >  -steve
>> > 
>> >  --
>> >  Steve Lianoglou
>> >  Graduate Student: Computational Systems Biology
>> > |   Memorial Sloan-Kettering Cancer Center
>> > |   Weill Medical College of Cornell University
>> >  Contact Info: http://cbio.mskcc.org/~lianos/contact
>> > 
>> >  ______________________________________________
>> >  R-help at r-project.org mailing list
>> >  https://stat.ethz.ch/mailman/listinfo/r-help
>> >  PLEASE do read the posting guide
>> >  http://www.R-project.org/posting-guide.html
>> >  and provide commented, minimal, self-contained, reproducible code.
>> > 
>> > 
>> > 
>>
>> 
>
>
>