Potentials - November/December 2016 - 15

32-b mbed NXP LPC1768 running
at 96 MHz from ARM Ltd., due to its
low price, small size, low power consumption, and, most of all, its relatively high computing performance.
This microcontroller, in particular,
is for prototyping all sorts of devices. It is armed with the flexibility of
plenty of peripheral interfaces and
flash memor y. The microprocessor includes 512-kB flash, 32-kB
RAM and interfaces including builtin ethernet, universal serial bus
(USB) host and device, controlledarea network, serial peripheral interface, inter-integrated circuit bus,
analog-to-digital converter, digitalto-analog converter, pulse-width modulation, and other input/output
interfaces. Most pins can also be
used as DigitalIn and DigitalOut
interfaces, which allows for easy addition of various sensors. The online
C++ software-development and compiling environment allows the development team to work on the project
anywhere and anytime.
The communication module is a
Bluetooth chip (or a Wi-Fi chip) that
allows the wearable unit to talk to
the smartphone to exchange data
and instructions. The LPC1768 microprocessor offers flexible hardware
interfaces for us to easily hook up
various lower-power-consumption
Bluetooth and Wi-Fi chips that are
available on the market, such as the
RN42-XV Bluetooth and the XBee
Wi-Fi module.

Power Module

The sensor module consists of
various smart sensors that we can
embed in the system to obtain data.
The ultrasound sensor detects objects and measures object distance

Continuously feeding the visually impaired user
with the necessary information about his/her
surroundings is critical for him/her to "feel" and
"sense" things nearby and move around without
bumping into objects and losing orientation.
from the unit. This is similar to sensors that are widely installed on vehicles to prevent collisions. In this
prototype, we used Ultrasonic Range
Finder XL-MaxSonar-EZ4. Other
sensors that we plan to use but have
not yet instituted include color sensors to detect traffic lights, motion
sensors to identify moving objects in
front of the visually impaired user,
and a camera that can be used for
image processing and identifying objects of interest.
The smartphone receives data obtained from the wearable smart sensor unit, processes the data in real
time, and generates and provides the
visually impaired user with critical
warning signals and other information to assist him/her in navigating
the surrounding area in the form of
voice and/or vibrating signals. For
instance, when the sensor detects
an object in front of the user within

mbed NXP LPC1768

Power LED

Communication
Module
Bluetooth
Chip

Switch
CPU

Battery

3 m, the smartphone sends beeps to
the user at a higher frequency as an
object gets closer. At the same time,
the smartphone utilizes its GPS and
map function to "talk" to the visually

Wi-Fi Chip

Sensor Module

impaired user, providing his/her
moving orientation and location
(such as street and building names).
The wearable smart-sensor unit
can be clipped on a pocket, belt, or
hat and faces the user's moving direction so that the ultrasound sensor can "see" the objects in front
of the user. The user should also
carry the smartphone appropriately
so that he/she can receive the correct moving orientation information.
These two units talk to each other
via Bluetooth; therefore, there is no
wired connection between them.
Figure 2 provides the details
of the circuit connection among the
LPC1768 CPU, the MaxSonar ultrasonic-range sensor, and the RN42XV Bluetooth chip. The ultrasonic
sensor's analog output (PIN-AN) is
connected to one of the CPU analog
inputs (PIN-19) for the CPU to read
the distance data of a detected object.

* Object Detected in Front
* Human Detected
* Traffic Light
(Bluetooth/Wi-Fi)

Smartphone

Sensor Interface

Ultrasound Sensor

Motion Sensor

Other Sensors

Fig1 the "virtual eyes" system structure.

IEEE PotEntIals November/December 2016

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Table of Contents for the Digital Edition of Potentials - November/December 2016