inferred by considering the following basic information:
(bed1_active(t) or bed2_active(t)) and shower_tap_active(t).
Specifically, bed1_active(t) and bed2_active(t) are true if the
pressure sensors located on either bed1 or bed2 detect
something, whereas shower_tap_active(t) is true if the
shower tap is opened.
● EXAMPLE 2: The user is in bed for longer than usual.
This situation can be modeled using such simple
information as: bed_active(t1) and length(bed_active, t).
length(bed_active, t) is true if the value of bed_active is
true for more than a given temporal threshold t. At the
time instant t1 the inhabitants are on the bed. As soon as
time passes, the value of bed_active remains unaltered. At
the time instant t2 such that t2 - t1 > t, length(bed_active, t)
becomes true (see Figure 2), thus inferring this situation.
● EXAMPLE 3: During the night, the inhabitant cannot
sleep; therefore, he gets up and decides to switch on the
TV in the kitchen. This scenario can be modeled using
very basic information as demonstrated in the previous
examples. As shown in Figure 3, relevant information
includes the change of the data value for bed_active (which
switching from true to false allows the system to infer that
the user got up from the bed) and an opposite change in
tv_on (from false to true, thus implying the use of the TV).
There is still a lot of work to do before ubiquitous
intelligent systems surround us and help us in our daily
activities. Although AmI is particularly young and
unexplored for the most part, its benefits are more than
evident. What is needed to make AmI a reality is for intrepid,
motivated innovators to move the field forward. SV
All photos are courtesy of Philips.
1. K. Ducatel, M. Bogdanowicz, F. Scapolo, J. Leijten, J.C.
Burgelman. Scenarios for Ambient Intelligence in 2010. IS TAG
Report. IPTS-Seville, February 2001.
2. D.J. Cook and S.K. Das. How Smart Are Our Environments?
An Updated Look at the State-of-the-Art In Pervasive and
Mobile Computing, vol. 3(2), pp. 53-73, March 2007.
5 reflectance sensors on underside
The Pololu 3pi robot is a high-performance, compact
mobile platform featuring:
Two metal gearmotors
Five reflectance sensors
8×2 character LCD
Three user pushbuttons
Buzzer and LEDs
All peripherals are connected to an ATmega168
microcontroller running at 20 MHz, with free C-programming push-on/push-off
tools, libraries, and support for the Arduino environment. power button
High-traction silicone tires
Speeds exceeding 3 ft/sec
using innovative constant-voltage motor supply
robot diameter is 3π cm (~ 3. 7 inches)
Find out more at www.pololu.com/3pi or by calling 1-877-7-POLOLU.
SERVO 12.2008 47