Personal Server
Intel Research
The Personal Server is a new class of mobile device that utilizes advances in processing, storage, and communication technologies to provide ubiquitous access to personal information and applications through the existing fixed infrastructure. The Personal Server possesses no display, allowing it to be smaller than traditional PDA-class devices; instead, it uses low-power short-range wireless for access to existing large-screen displays, such as those found on laptop computers or desktop PCs. The personal server is a pocket sized device that provides information we need right at our fingertips that can be accessed from any workstation, anywhere in the world.
CENS
(Center for Embedded Networked Sensing)
CENS at UCLA is developing Embedded Networked Sensing Systems and applying this technology to critical scientific and social applications. These large-scale, distributed, systems, composed of smart sensors and actuators embedded in the physical world, will eventually infuse the entire world.
Broadband Seismic Network - Mexico Experiment.
The CENS data communications controller utilizes a Stargate. The CDCC is capable of wireless networking from tens of meters to tens of km. The CENS timing synchronization software has undergone successful tests with the objective the network can operate without access to GPS time, e.g., underground. CENS has joined California Institute of Technology and Universidad Nacional Autónoma de México (UNAM) to apply the seismic networking technology to a sesmic array study in Mexico. 50 units have been shipped to Mexico City.
NIMS (Networked Infomechanical Systems)
The Networked Infomechanical Systems Program focuses on distributed embedded sensors that are intended to acquire information regarding signal sources and events associated with sources in the environment.
As distributed embedded sensor technology has appeared, the first challenges confronting their successful deployment have been addressed. This has included development of energy-aware architectures for long lived, unattended operations and scalable networking for pervasive deployment. Also, distributed algorithms enabling cooperative detection by networked embedded sensors have been developed. However, as embedded sensors have been deployed in environments, a new set of problems associated with their most essential information return capability has emerged.
One of the most important challenges include sensing uncertainty that arises from the unpredictable and time-variable nature of obstacles to sensing. Sensing uncertainty degrades the performance of event detection and the capability for sensor data fusion for event characterization.
Emstar
EmStar is a software system for developing and deploying wireless sensor networks involving Linux-based platforms. EmStar is a Linux-based software framework, whose goal is to dramatically reduce this complexity, enabling work to be shared and reused, and simplifying and speeding the design of new sensor network applications.
PER
Personal Exploration Rover
CMU
You can travel to several sites where you will be able to interact with Personal Exploration Rovers. Our educational goals include demonstrating the role of rovers as science tools to the public and demonstrating the need for on-board rover autonomy during Mars missions.
EcoSense
Intel Research
“If it’s difficult to transmit data reliably across a network of 50 nodes, what happens when you build a network of 500 or 5,000 sensors?” The project team is tackling a difficult challenge: how to network large numbers of inexpensive wireless sensor nodes while maintaining a high level of network performance. Intel researchers are exploring the concept of heterogeneous networks. The concept is simple: an 802.11 mesh network comprised of high-end nodes, such as Intel® XScale™ based nodes, is overlaid on a sensor network.
Place Lab
Intel Research and University of Washington
Place Lab is a software base and a community-building activity that facilitates widespread adoption of low-cost, easy-to-use user positioning for location-enhanced computing applications. Unlike existing indoor and outdoor user-positioning systems, Place Lab endeavors to provide planetary-scale and privacy observant user positioning by making use of existing infrastructure and offering a low barrier to participation. Furthermore, Place Lab allows clients to determine their location entirely privately without constant interaction with a central service. The key motivation for Place Lab is the widespread proliferation of WiFi technology. Leveraging this ubiquitous deployment of WiFi access points, Place Lab provides a way for a WiFi-enabled client device to automatically determine its position.
IRISNet (IR
site)
Intel Research and CMU
IrisNet (Internet-scale Resource-Intensive Sensor Network Services) is focused on harnessing a global sensor network much like one queries on the internet.. Webcams and other sensors are spread throughout the environment, collecting vast amounts of potentially useful data, but there are no effective tools to query the data. The IrisNet research team is developing a scalable software infrastructure that will enable users with Internet access to query Webcams and other globally distributed collections of high-bit-rate sensors.
Kansei
Testbed
Ohio State University
The Kansei provides a testbed infrastructure to conduct experiments for the 802.11b network. Currently, Ohio State is using it to test the middleware services for the Tier-2 network for the Extreme Scale project funded by DARPA.
Exscal
It is widely believed that someday there will be sensor network deployments of hundreds of thousands of nodes. The challenges in scaling to networks of this size are quite different than the ones encountered in fielding much smaller networks of dozens or hundreds of nodes. The former subsumes the latter and add a host of new problems. The motivation for the DARPA Extreme Scaling project, code-named "Echelon," is to investigate the challenges in scaling to a network of 10,000 sensor nodes.
HiFi
UC Berkeley
Advances in data acquisition and sensor technologies are leading towards the development of High Fan-in architectures: widely distributed systems whose edges consist of numerous receptors such as sensor networks and RFID readers and whose interior nodes consist of traditional host computers organized using the principle of successive aggregation. Such architectures pose significant new data management challenges. The HiFi system, under development at UC Berkeley, is aimed at addressing these challenges.
We use Stargates as our mid-tier, initial processing nodes. Furthermore, we have demoed this system, with Stargates and all, at a major database conference recently.
Robotics
Stanford AI Research Lab
The Stargates are part of vehicle used by Stanford's Grand Challenge Team. They are used to deal with a complex sensor issue involving laser sensor control and sun light. They are also on our helicopter and are currently ported to a small quadruped robot that is in development.
Intel Mote
The Intel Mote project team seeks to create a new platform design that delivers a high level of integration as well as low-power operation in a small physical size. Features of the new platform include modular hardware and software design; system power management; and low-cost, high volume production potential.
WEBS
Wireless Embedded Systems
UC Berkeley
The primary objective of the Intel® Mote research project is to build an enhanced generation of the “mote” technology originally developed through the collaborative efforts of the University of California Berkeley and the Intel Research Berkeley laboratory. Motes are tiny, self-contained, battery-powered computers with radio links, which enable them to communicate and exchange data with one another, and to self-organize into ad hoc networks. Motes form the building blocks of wireless sensor networks.
TASK
Intel Research Berkeley
Real users of sensor networks ranging from plant biologists monitoring micro-climates in a giant redwood tree to facility managers monitoring vibration signatures of their equipments are most likely not sophisticated software developers. We must reduce the complexity of sensor network application development and deployment to ensure the success of sensor network technology in the real world.
REKF-Localization
We are developing a novel localization system for sensor networks in which we can use a mobile robot to perform location estimation for sensor nodes it passes by, using the radio signal strength of the messages received from them. Thus, we eliminate the processing constraints of static sensor nodes; and also the need for static reference beacons. By using a mobile robot, we also eliminate many of the problems associated with using RSSI measurements, such as small-scale fading. To solve the localization, we use a novel mathematical technique, the Robust Extended Kalman Filter (REKF). REKF is computationally efficient and more robust than the more commonly used traditional Kalman Filter.
Search
and Rescue
University of Waterloo
The Department of Systems Design Engineering at the University of Waterloo has developed the SPIDER ET Robot, a rough terrain, small-sized, low power mobile robot which is able to traverse, climb and descend elevation changes, use computer vision to navigate, locate people, establish context, localize and build maps. It is an augmentation of the Bluebotics “Shrimp robot” including on-board, low-power electronics with a small embedded computer; various accelerometers; a stereo microphone; wireless communication; a camera system; and the software used to control the robot. One application is to act as a first look system when co-operating with a human search and rescue team, communicating with the human team so that when humans enter they are prepared and safe.
