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An interesting article about consumer patterns is presented in [10]. The au-
thors employed a wireless local area network (WLAN) to obtain the data from
a shopping environment. They results show how the consumer behavior varies
depending on the time of the day. In their work, they divided the consumer
behavior into three segments: (1) 8:00 am to 12:00, (2) 12:00 to 16:00 and (3)
16:00 to 20:00 and presents the obtained tracking results of each segment on
the shop ground plane. Our work, go further since it automatically discover the
occupancy patterns on the sensor data.
Farrahi and Gatica-Perez [11] presents an interesting work in the mobile do-
main using also the LDA model to discover routines. The method used for gener-
ating the bag-of-words before training the model inspired the approach presented
in our work. Their results also supports the advantage of using LDA for discover
routines on large amount of data.
3 Building the Representation of the Long-Term
Behavior Model
The long-term-behavior model is constructed using terms which are commonly
employed in the information retrieval community: words, documents, topics and
corpora. That is, in the context of this work
”words”
refers to occupancy patterns
or location sequences over some time interval. A
”document”
refers to a complete
day of words (location sequences) for a specific room. The
”corpora”
is the full
data obtained from the sensors, that is the set of all documents. Finally, the
”topics”
are equivalent to the routines and the main task is to automatically
infer them. So, the aim is to learn both what the topics are and which documents
employ them in which proportions.
Each possible word
w
, of the vocabulary
v
, is generated taking intervals of
30 minutes which consists of three sequences of 10 minutes of occupancy over
each room. The whole weekday is divided into 9 segments of day following this
scheme:
1. from 00:00 to 06:00, interval 1.
2. from 06:00 to 07:00, interval 2.
3. from 07:00 to 09:00, interval 3.
4. from 09:00 to 11:00, interval 4.
5. from 11:00 to 14:00, interval 5.
6. from 14:00 to 17:00, interval 6.
7. from 17:00 to 19:00, interval 7.
8. from 19:00 to 21:00, interval 8.
9. from 21:00 to 00:00, interval 9.
So, the words generation approach of the vocabulary follow this structure: com-
binations of 3 sequences of
(empty room) symbols,
plus the segment time of day number (one of the previous 9), plus the room num-
ber. For instance, the word
I
(someone in the room) or
O
refers to 30 minutes of no occupancy at
the time interval 1 (from 00:00 to 6:00) for the room number 120; and the word
OOO1120
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