[R] Temperature Prediction Model

Aneeta anestays at cs.sunysb.edu
Mon Oct 26 06:21:59 CET 2009


Thank you everyone for all the responses.

Clint you are correct in assuming that the problem deals with sensors in a
lab setup which can be assumed to be isolated from outside temperature
changes. And, I am only dealing with temperature so the other parameters are
not important.

There will be no gorillas or mouses in the picture but rather some malicious
attacker who would try to cause disturbances in the normal readings. That is
why it is important to have an equation that defines 'normal behaviour'.

The data-sets contain readings for multiple days. I want to take the first 7
days for each node and establish a relationship between time(column 2) and
temperature(column 4). 

My objective is not to model temperature variation throughout the year and
take into consideration climatic changes. Rather, it is to define a model
for the given data which happens to be temperature recorded by nodes. In a
simple way we may look at it as a set of X(time) and Y(temperature) values
where I am trying to define Y in terms of X.

How should I approach this problem?

Many Thanks,
Aneeta


Clint Bowman wrote:
> 
> 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.
>>> > 
>>> > 
>>> > 
>>>
>>> 
>>
>>
>>
> ______________________________________________
> 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.
> 
> 

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