>The Smart Fence
Conventional security systems have limitations. For example, in an
industrial setting, fence monitoring using video surveillance becomes
expensive and inefficient as the area under observation grows to
cover several miles in length. The goal of this project is to provide
a sensor network approach to this problem. Using WirelessHART compliant
communication nodes and cheap MEMS-based accelerometers, the solution
covers recording vibrations locally on each fence section and
relaying the readings back to a central computer for processing and
detection. For the detection algorithm, decentralized sequential
hypothesis testing was selected because it performed well both during
testing and real deployments. In essence, the sensors communicate
only when a decision is made concerning the observed event. Those
decisions are then fused at the sink which raises the alarm or not.
A long term deployment proved the applicability of this algorithm
with 100% detection rate and 0% false alarms.
>Wireless Sensing Applications for Critical Industrial Environments
Following the successful showcase of the Smart Fence technology,
this project aims at using MEMS and Electro-Chemical Sensors in
combination with Low-Power radios to implement industrial wireless
sensing applications. In particular, and at the Chevron-Richmond
refinery, fence-line gas sensing is added to the previous security
application with regular reporting of H2S, CO and VOC concentrations.
Using MEMS accelerometers and magnetometers, valve position monitoring
and machine vibration sensing are added for safeguarding both personnel
and equipment. This project is concerned both with the COTS-based
hardware and software behind each application.
Being part of the WSN group
at UC Berkeley, I am also a contributor to the open-source initiative
taken by Thomas Watteyne to publish a standards-based protocol stack for
Wireless Sensor Networks. The source code, documentation and everything
you need to know about this type of networks can be found at http://openwsn.berkeley.edu.
>Video over WSN
Tired with all the speculations around wireless sensor networks, we
decided it was the time to demonstrate it was actually possible to
transmit video over a multi-hop low power network. Not only did we
succeed, but we did all of this using a standardized protocol stack. We
summarized the results in an IEEE Comsoc E-letter that you can find in
my publications page.
The US-DOT started a program to develop Intersection Decision Systems to
address accidents that take place at those facilities. The UC Berkeley
transportation department (under CEE), along with Caltrans and CA-PATH
took up the "Signalized Left Turn Assist" aspect of this initiative. In
broad terms, what we would like to do is sense whether we have people
waiting to make a left turn at the intersection, then tell those
motorists whether or not they have a big enough gap in the oncoming
traffic to complete the maneuver safely. Of course, magnetometers and
TSCH (time-synchronized channel hopping) came to the rescue. The study
is reported in a paper that you can find also in my publications page.