Ice scream, you scream...

Being a native California driver I rarely encounter icy road conditions unless I'm on my way to Tahoe to go snowboarding or skiing. I remember the day we had snow in the Bay Area and everyone ran outside to experience the phenomenon (although it only lasted on the ground for a few moments before melting away). In many parts of the world icy road conditions prevail and the ability to easily monitor and detect the danger is not easy due to the harsh environment. However, the idea of pavement condition monitoring would save many a spinning car and screaming driver from sliding on the ice into the side of the road.

Pavement maintenance is vital for travel safety. By using wireless sensor networks to monitor pavement temperature and moisture presence, icy road conditions can be detected. It is essential to provide warnings of dangerous traffic conditions in real-time. In a study done at University of Oklahoma, researchers determined to investigate a densely distributed sensor network and classify pavement conditions into certain categories - 1) dry 2) wet and 3) frozen.

This project was deployed with the MICA2 Motes from Crossbow while integrating them with various 3rd party sensing devices using the MDA100 prototyping board. The ability to integrate 'alien' sensors to the Mote platform gave the researchers the flexibility they needed to complete the task at hand. The sensors chosen to provide the data included a thermistor to gather temperature readings, a leaf sensor to detect the conductivity of a wet pavement to detect the existence of free moisture and an infrared sensor to detect ice by emitting a near infrared light that is reflected by the ice and detected by the infrared receiver (water is transparent to the receiver).

An integrated sensor and road button structure housed the 3 sensors as shown in the figure above. The top surface of the sensor road button contained the moisture and infrared sensors with the thermistor at the bottom. Due to the low power consumption of the sensors used, these devices were powered by the MICA2 Mote platform. The Mote platform was placed into a protective watertight aluminum casing with upgraded antenna doubling the Motes transmitting range.

When collecting readings from the sensors, the Mote transformed them into digitized data, sent them to the radio and waited until all data was sent before switching to sleep mode. In detail, the processor received sensor readings from the embedded 10-bit Analog-to-Digital Converter (ADC). If the data was taken correctly, the onboard light emitting diodes (or LEDs) lit up to signal the proper functioning of the mote. Analog to digital conversion was performed on the readings, after which the data was integrated into the packet to be transmitted. The default packet format was slightly modified to fit the size and format of the data to be transmitted. The packet was then sent to the radio and transmitted over the network until it reached the base station. The base station was connected to a laptop through a serial port. The data was then collected using a LabVIEW graphical user interface (GUI) developed for this project. Raw data from the serial port was collected, deciphered and displayed by the GUI.

Using the MICA2 Motes to monitor the pavement conditions is a unique application; therefore, the aforementioned features (directly applying time synchronization and embedding a pattern classification algorithm) further distinguish this study from existing research that utilizes Motes in real-world applications. A series of laboratory tests was conducted at the Asphalt Laboratory at the University of Oklahoma using an environmental chamber to study the effect of temperature and moisture on the sensors (and later, the motes). The environmental chamber was used to produce well-controlled temperature and humidity variations. The sensor-road button unit was tested to (1) test the full functionality when all the sensors were combined together, and (2) collect data to aid refinement and further development of the proposed ice detection algorithm proposed in this application. The entire lab test was completed in a four-hour time frame. Note that weather changes in reality could be much slower than this testing rate; thus such a test could be more stringent than a real-world situation.

A series of outdoor tests were conducted as well paying special attention to the packaging and survivability of fragile analog sensors in harsh roadway conditions and how they will be utilized in other applications of intelligent transportation systems (ITS) as well as structural health monitoring. These methods allowed the Mote wireless sensor network to be easily installed and provided a robust solution to environmental factors such as wind and rain. Imagine a day when roads are 'smart', when you are told exactly what conditions to expect before you encounter a patch of ice. It is this concept and future that we envision with the Mote platforms - a smarter safer future that we all can scream for!

Who needs The Club when you've got SVATS!

According a report by the FBI, a vehicle is stolen every 26.4 seconds in the United States. The western states account for the highest rate of thefts in the USA, and 4 of the top 10 metropolitan areas were in California - made me feel very safe! Remember 'the club' from back in the day? I remember watching the commercials when I was a kid between episodes of Saved by the Bell and thinking that my parents should get one - it seemed like the perfect solution. Check out this commercial from the nineties (love the hairstyles and outfits).



Luckily today, things have progressed, and instead of having to whip out your club and strap it to the steering wheel of your car, you can install SVATS. SVATS is a sensor-network-based vehicle anti-theft system based on Crossbow's MICA2 Mote platform. Conceptualized by researchers at Penn State University, SVATS is designed to address the limitations of high cost, high false-alarm rate and the easy disabling function of current tracking/alarming systems. In this system, the vehicles in an area are outfitted with a sensor node and form a wireless sensor network. The nodes in the network then monitor and identify possible vehicle thefts by detecting unauthorized vehicle movement. When an unauthorized movement is detected, an alert is sent to the base station which sends warning messages to the security office or whomever is responsible for that area. The security system relies on networks of cars constantly gossiping with their neighbors using the concealed wireless nodes. The cars raise the alarm when a thief tries to make a getaway.

With vehicles playing an essential part in our every day life, there are many solutions to stop theft from lock systems (like the club), alarm systems (that we all ignore nowadays) and vehicle tracking/recovery systems. Most of these tracking/recovery systems require the user to purchase the product as well as pay a monthly maintenance fee, or use GPS which does not work indoors or is easily located and disabled. SVATS proposes to have a each vehicle equipped with a node, and each parking area forming its own sensor network with base station. Each node is powered by the vehicle's power source and controlled by a remote so that the user can turn it on so that the node sends a 'join' message and broadcasts its 'alive' message periodically. If it does not send out a 'leave' message that is authenticated by the user via remote that turns the node off, the neighboring sensors will detect the movement or should they not receive the 'leave' message report the problem to the base station and owner via alert. To track the vehicle SVATS used roadside access points already deployed to determine where the vehicle had been moved to. The researchers themselves drove off some cars to test how the system worked, and found that SVATS detected all such "thefts" in a matter of just 4 to 9 seconds. The system was apparently resistant to false alarms caused by weather, or people walking around the car park, both of which can affect the signals between sensors.

SVATS included four components network topology management, vehicle theft detection, intra-vehicle networking, and alert reporting. Using the MICA2 Mote platform in the sensor node for this deployment, researchers were able to use the self-forming, ad-hoc capability of the Motes to allow the device to find its neighbors and join the network. The vehicle theft detection was done with two techniques - count-based and statistical-based. RSSI signals and values were also used to determine whether a vehicle had been stolen or not. The system can also detect when a car is moving unexpectedly by measuring the signal strength of any "alive" messages. If a car detects significant changes in signal strength, it sends a warning message to other cars monitoring the same vehicle, because it is likely to be moving. However, it is only when a watching car receives more than three such warning signals from different sources that it will send out a theft alarm message to the base station. Ensuring that multiple cars must agree on a threat before the alarm is raised should cut out the false alarms that plague other anti-theft systems, say the researchers. Experimental evaluation of the SVATS system used a laptop as a base station and one sensor per vehicle in a Penn State parking lot.  The base station transmitted once per second while the vehicle sensors sent live messages every 200 milliseconds.

The key to SVATS is that the sensor nodes are cheap and easy to deploy. They are designed to work in a large network that creates a smart and safe environment. This solution can be deployed incrementally and the rapid response time it provides is motivation enough to install the SVATS sensor nodes. This research was funded by NSF and the Army research office. The researchers presented information on their system at the Institute of Electrical and Electronic Engineer's Infocom 2008 Conference in Phoenix.  

As one person said, stealing a car wont be easy for thieves anymore, thanks to this new type of car alarm that enables the vehicles to look after each other"s safety - just like a herd of animals under any potential threat from predators.

Smart Attire - Bringing Technology Into The Closet!

What is smart attire? To some it may be clothes that tell you when they are mismatched, or that figure out how to conform to your body type or inform you that these clothing articles do not belong on your body unless you look like Gisele Bundchen. Smart attire like that would soon get rid of the numerous 'What not to wear' blogs and shows we watch, but unfortunately, that is not what we are talking about today. Smart Attire is the next generation of attire that will embed computing and sensing power in clothes, aiding in the development of novel personal monitoring services such as healthcare for the elderly in the comfort of their own home, safety of people working in dangerous situations such as firefighters, construction workers, etc., personal and medical monitoring for joggers, bicyclists, etc. and even entertainment in offering a personal tourist guide system or for social networking. Smart attire can be useful in many ways to help, benefit and entertain those that use them by personally monitoring their environment and bringing technology into their wardrobe.

The feasibility of embedding clothes with computing devices has come about due to the continued revolution of the decreasing sizes of these devices. This allows the device to be unobtrusive to the wearer. Researchers at the University of Illinois, Urbana-Champaign have developed a Smart Jacket. This piece of clothing is built by weaving MICAz Motes into the lining and padding of a winter jacket. As the size of Motes continue to decrease the goal is to embed these devices in shirts, pants, etc. The jacket prototype developed is capable of monitoring the motion and location information of a person remotely by using accelerometers and a GPS sensor with Crossbow's off-the-shelf sensor hardware such as the MTS310 or MTS420 sensor boards. A typical scenario would be of a person wearing the jacket outdoors while it records the motion and location information in the flash memory of the MICAz Motes. Upon coming into range of the base station, the data collected is uploaded to the PC transparently.

The idea of clothing with sensors and computing devices embedded in them is exciting. The idea is not to create a jacket with gizmos like Inspector Gadget, but to embed sensing into these items. With the development of smart attire that not only integrates technology, but is the technology - it is necessary to develop software to interpret the data collected by the clothing. Hence the development of SATIRE - a software architecture for smart attire. As personal instrumentation and monitoring services that collect and archive the physical activities of a user continue to become more popular, a general software architecture is needed to support the different categories of monitoring services. SATIRE is a personal monitoring service that records the owner's activity and location for subsequent automated uploading and archiving.  It allows users to maintain a private searchable record of their daily activities as measured by motion and location sensors; the goal is to perform this data collection in a manner that is transparent to the user when they come into range of the base access Mote at home. To identify the human activity from accelerometric data is difficult; therefore the SATIRE system uses Hidden Markov Models (HMMs) which is still in development. Future work for this project includes the development of security and privacy policies as well as the identification of more sophisticated activities.

A brief video of the prototype can be seen here:

SATIRE implements remote data logging of daily activities and location information, upload protocols for the raw sensory data collected and the use of sophisticated algorithms to interpret the data and make useful deductions to reconstruct activities from the smart attire. The software architecture developed is flexible and modular for future development of smart attire systems that simplify the introduction of new sensors and new algorithms. To get more information on SATIRE visit the project site here where you can download TinyOS for SATIRE as well as view information on installation and usage of this platform. The future is here - bringing technology into the closet!