iMouse - Integrated Mobile Surveillance and Wireless Sensor System

Surveillance systems have always seemed like something out of a James Bond movie to me - a system that observes events without being intrusive but is able to capture valuable data that allows people to save the world from sure catastrophe (like the time I forgot to open the flue for the fireplace and almost burned smoked out the house)! Surveillance systems are used to monitor or observe the behavior of persons, processes, places, objects, etc. to determine whether they are functioning normally or if there is any deviation from their standard behavior.

It is this concept and its integration with wireless sensor networks that researchers at National Chiao Tung University are addressing to develop their iMouse platform, an  integrated mobile surveillance and wireless sensor system. Incorporating the environment-sensing capability of wireless sensor networks into video based surveillance systems provides advanced services at a lower cost than traditional systems. The iMouse's integrated mobile surveillance and easy to deploy wireless sensor system uses static and mobile wireless sensors to detect and then analyze unusual events in the environment. Wireless sensor networks (WSN) provide an inexpensive and convenient way to monitor physical environments. The iMouse system, consists of a large number of inexpensive static sensors and a small number of more expensive mobile sensors. The former is to monitor the environment, while the latter can move to certain locations and gather more advanced data. The iMouse system is a mobile, context-aware surveillance system.

The three main components of the iMouse system architecture are (1) the static sensors, (2) the mobile sensors and (3) an external server. The system is set up so that the user could issue commands to the network through the server at which point the static sensors would monitor the environment and report events. When notified of an unusual event or change in behavior, the server notifies the user and dispatches the mobile sensors to move to the emergency sites, collect data and report back to the server.

Each static sensor is equipped with Crossbow's MICAz Motes, available in our WSN-START and WSN-PRO development kits, and a sensor board.The static sensors are placed in known locations which can be established through manual setting, GPS or localization schemes. The static sensors can then determine which sensory input is higher or lower than the predefined threshold. For example, a sensor can interpret a combination of light and temperature readings as a potential fire emergency. To detect an explosion, a sensor can use a combination of temperature and sound readings. Or, for home security, it can use unusual sound or light readings. The mobile sensors consist of Crossbow's Stargate Platform, a Lego car, a MICAz Mote, a webcam and IEEE 802.11 WLAN card to support high-speed, long-distance communications such as transmitting images. These mobile sensors can move to event locations, exchange messages with the other sensors, take snapshots of event scenes and transmit the images. The Stargate controls the movement of the Lego car and the webcam while the MICAz Mote is used to communicate with the static sensor nodes.The external server provides an interface to obtain system status and issue commands.It also maintains the network and interprets the sensor data. The researchers at National Chiao Tung University have developed the dispatch algorithms and user interface to establish the system operation and control flow.

The iMouse system integrates mobile WSN technologies into surveillance technologies to support intelligent mobile surveillance services. This is made possible by the easy to deploy capability of the Mote platform and its flexibility to be integrated into various applications. It is this type of research that is paving the way for future technologies to provide us with more accurate and detailed data about the environments and processes that surround us.

Crossbow's Imote2 wins 'Best of Sensors Expo' award

Crossbow Technology's Imote2 platform was nominated for the "Best of Sensors Expo" award in the 'Communications and Networking' category.  The "Best of Sensors Expo"€ Awards honor the most exciting new products on display at the Sensors Expo and Conference, which took place at the Donald E. Stephens Convention Center in Rosemont, IL, last week. On Wednesday, June 13th, the awards were announced and the Imote2 platform received a bronze award for its breakthrough capabilities.

The Imote2 platform, which was commercially available at the end of March, is a high-performance wireless sensor network node that provides a high-throughput processor and radio platform which breaks the computational and memory limitations of current platforms by orders of magnitude while enabling low-power operation for battery-powered sensor network applications. Crossbow also offers a companion sensor board with 3-axis accelerometer, temperature, humidity, light and four channels of user-customizable A/D input. Based on the Marvell PXA architecture, it supports a 250kb/s data rate with an IEEE 802.15.4 compliant 2.4GHz band radio.  Full 32-bit computing is supported at speeds up to 416 MHz.  The Imote2 provides the most extensive support for development environment / operating systems, including TinyOS, SOS, and Linux.  The Imote2 is used for advanced, compute-intensive wireless sensor applications such as digital imaging, industrial vibration monitoring, seismic and acoustic based signal processing, and machine condition monitoring. The Imote2 provides the highest performance, lowest power wireless sensor solution compared to existing alternatives in the market today.

At Sensors Expo, Crossbow announced the Imote2.Builder for the .NET Micro Framework, the Imote2 SDK based on the Microsoft .NET Micro Framework. The Imote2.Builder is the industry's first set of tools for accelerating the development of entirely new wireless sensor applications on the Marvell PXA hardware platform on which the Imote2 is built. The .Builder kit simplifies and accelerates the design of wireless sensor applications by combining two powerful ingredients to create a superior embedded design: Crossbow's Imote2 hardware module and the Microsoft .NET Micro Framework software. Together they provide new developers with an industry-leading development experience for rapid prototyping of wireless sensor applications by creating proof of concept in hours or days, not weeks or months, as well as quick, familiar debugging using Microsoft's Visual Studio environment to shift the focus to the code, not the tools. The Microsoft .NET Micro Framework combines the reliability and efficiency of managed code with the premier development tools of Microsoft Visual Studio to deliver exceptional productivity for developing embedded applications on small devices.

The award indicates Crossbow's continued efforts to provide our customers with cutting-edge leading technology that addresses the demands for wireless sensor networks in the market today. Crossbow's complete portfolio of research and development platforms, to our wide selection of commercial-grade hardware and software tools, give customers the ability to fulfill all their WSN product needs quickly and easily.

BehaviorScope - Using WSN to Recognize Human Behavior

As pervasive as radios, sensors and computing devices are in our day-to-day lives, humans still do not have a solution for a computing system that can operate autonomously as it observes the environment and acts on its own data analysis. This future concept is being taken on by the BehaviorScope project at Yale University's Embedded Networks and Applications Lab (ENALAB) as it aims to create a new breed of intelligent sensor networks that can understand and respond to complex behaviors, especially of humans, taking place in the physical world. The goal of the BehaviorScope architecture is to compose a number of heterogeneous sensor nodes into an asynchronous distributed computer that acquires its instructions directly from the physical world. By following a process analogous to speech recognition in digital voice applications, the BehaviorScope tries to parse motion patterns (as well as other virtual patterns) taking place in space and time into a set of predefined actions. Using these recognitions, a sensor-actuator network will be able to respond to different behaviors to provide services.

Using a combination of sensing, data processing and middleware services, the BehaviorScope interprets simple low-level sensor data into complex high level activity interpretations. In addition to its interpretive power, this conversion of raw sensor data into a more compact semantic form dramatically reduces the amount of data a network has to transport allowing multiple nodes to reason together about an activity by exchanging low bandwidth symbolic information. The framework converts the sensor network into a rule-based system where appropriate combinations of rules provide the descriptions for complex behaviors the system needs to detect. Researchers at ENALAB have already demonstrated a prototype of the BehaviorScope executing on a lightweight network of camera sensor nodes that use the Imote2 nodes provided by Intel and Crossbow.

In the current BehaviorScope deployments, a small network of privacy preserving camera sensor nodes track people around the house during the course of the day. The observations are used in the context of the building map to create detailed daily activity summaries and to generate alarms and cell phone notifications when safety conditions are violated. The ENALAB researchers are currently working with a team of doctors to create a comprehensive library of behaviors. Multiple instances of the system are deployed in different homes and behaviors are programmed using high level scripts that allow domain experts to concentrate on the applications functionality without having to worry about low-level node code. In addition to assisted living, the BehaviorScope architecture is expected to find applications in security, workplace safety, entertainment and other domains.

Difference aspects of the BehaviorScope project are currently funded by the National Science Foundation (NSF), the Machine Intelligence Community (MASINT) and through equipment donations by Intel and Crossbow. More information and updates on the project, including hardware and software releases can be obtained at the BehaviorScope website.