This paper describes the design and empirical evaluation of PHASER - a mote prototype for low-power directional communication in wireless sensor networks. PHASER has a modular design that includes three components: a low-power radio, an RF signal processing chip, and two off-the-shelf antennas. Directional communication is achieved by splitting the output signal from the low-power radio chip and controlling programmatically the phase of each signal as it transmitted to each antenna. The net effect of controlling the phase of the signals is that they generate patterns of constructive and destructive interference as signals propagate. PHASER is well-suited for wireless sensor networks as it does not require heavyweight signal processing techniques and consumes minimal additional energy. We have extensively evaluated the performance of five PHASER prototypes. Empirical results clearly demonstrate that changing the phase configuration of PHASER can generate diverse anisotropic radiation patterns. The diverse radiation patterns may be used to increase the signal strength at an intended receiver. Our data indicates that the signal strength of a link can be increased by at least 13 dBm. We also show it is possible to take advantage of the anisotropy of the radiation patterns to facilitate spatial reuse. More importantly, we show that the quality of the links from the same PHASER mote has a common pattern that can be predicted using a simple model. Our evaluation shows that model introduces an median absolute error of about 2 dBm. The model may be used for realistic simulations or integrated into protocol stacks to identify the phase configurations that improve link quality or spatial reuse.

We propose a hybrid architecture of wired and wireless sensors for smart fabric with applications including body dynamics and shape monitoring and patient rehabilitation. Our system is capable of acquiring data from up to 200 on-body sensors with 50Hz sampling rate using conventional low-cost hardware. The sensing and data processing is done in real time and the results available on a smaptphone, tablet or pc in 3D visual form or as alerts. The user experience of the demo will include trying out smart clothing that is enabled with the shape sensing fabric and observing the body shape dynamics on-screen in real time.

Energy saving and reliable long distance wireless communication are essential problems in wireless sensor networks (WSN) because of limited energy availability in the wireless sensors and application-specific requirements for faster, farther, and more reliable communication. We propose use of electronically controlled variable reactance passive elements antenna array (PEAA) [1, 2] for use with sensor nodes to achieve better wireless coverage and reduce energy expenditure during transmission and reception of data over wireless communications. Although the idea of using PEAA for WSN is not new [3] In contrast, we have developed and tested SAntArray: a working prototype of the antenna for WSN that has a novel digital direction controll.

Often software for wireless sensor networks (WSNs) is developed using a specific event based operating system (OS) such as TinyOS. However, this requires steep learning curve for the new developers. Other operating systems for embedded devices have limited support for new hardware platforms. Our goal is to provide an operating system for resource constrained devices that is easy to use for the wide range of researchers and developers familiar with C programming language and Unix operating system concepts. In addition, we provide a framework for agile portability to new hardware platforms, due to the nature of WSN systems that require specific hardware or features for the sensing tasks at hand. We propose Multiple agent netted sensor Operating System (MansOS), that demonstrates ability to execute the same application on different platforms including x86 CPU based computers for easy simulation and debugging of a single node or a whole network. The new platforms are easily added to MansOS thanks to the well defined abstraction layers. MansOS is being successfully used in real world applications, such as wild animal tracking and environmental monitoring in a fruit care research garden. It has also been used in academic environment for teaching wireless sensor networks.

Staff shortages and an increasingly aging population are straining the ability of emergency departments to provide high quality care. At the same time, there is a growing concern about hospitals' ability to provide effective care during disaster events. For these reasons, tools that automate patient monitoring have the potential to greatly improve efficiency and quality of health care. Towards this goal, we have developed MEDiSN , a wireless sensor network for monitoring patients' physiological data in hospitals and during disaster events. MEDiSN comprises Physiological Monitors (PMs), which are custom-built, patient-worn motes that sample, encrypt, and sign physiological data and Relay Points (RPs) that self-organize into a multi-hop wireless backbone for carrying physiological data. Moreover, MEDiSN includes a back-end server that persistently stores medical data and presents them to authenticated GUI clients. The combination of MEDiSN's two-tier architecture and optimized rate control protocols allows it to address the compound challenge of reliably delivering large volumes of data while meeting the application's QoS requirements. Results from extensive simulations, testbed experiments, and multiple pilot hospital deployments show that MEDiSN can scale from tens to at least five hundred PMs, effectively protect application packets from congestive and corruptive losses, and deliver medically actionable data.

Staff shortages and an increasingly aging population are straining the ability of emergency departments to provide high-quality care. Moreover, there is a growing concern about the ability of hospitals to provide effective care during disaster events. Tools that automate patient monitoring would greatly improve efficiency, quality of care, and the volume of patients treated. Towards this goal, we have developed MEDiSN, a wireless sensor network for monitoring patients' vital signs in hospitals and disaster events. MEDiSN consists of Patient Monitors which are custom-built, patient-worn motes that sample, compress and secure medical data, and Relay Points that form a static multi-hop wireless backbone for carrying patient data. Moreover, MEDiSN includes a back-end server that persistently stores medical data and presents them to multiple GUI clients. MEDiSN's heterogeneous architecture enables it to address the compound challenge of reliably delivering large volumes of data while meeting the application's QoS requirements.

Environmental wireless sensor network (EWSN) systems are deployed in potentially harsh and remote environments where inevitable node and communication failures must be tolerated. LUSTER---Light Under Shrub Thicket for Environmental Research---is a system that meets the challenges of EWSNs using a hierarchical architecture that includes distributed reliable storage, delay-tolerant networking, and deployment time validation techniques.

Wireless sensor network (WSN) applications are notoriously difficult to develop and debug. This paper describes Clairvoyant which is a comprehensive source-level debugger for wireless, embedded networks. With Clairvoyant, a developer can wirelessly connect to a sensor network and execute standard debugging commands including break, step, watch, and backtrace, as well as new commands that are specially designed for debugging WSNs. Clairvoyant attempts to minimize its effect on the program being debugged in terms of network load, memory footprint, execution speed, clock consistency, and flash lifetime.

In this paper we address three challenges that are present when building and analyzing wireless sensor networks (WSN) as part of ubiquitous computing environment: the need for an in-situ user interface, a data logger, and a power consumption meter. Solutions for the above have been presented using laptops, personal digital assistants (PDA), onboard flash memory chips of limited size (usually 1MB), and laboratory test equipment. All of them have a good utility for the right applications. However, considering a certain variety of WSNs, where size, battery life, and cost are crucial, none of the above solutions is satisfactory. In this paper we present a compact, lightweight, low power, and low cost multimodal sensor module SeeMote that meets the stated challenges, and is compatible with the popular MICAz mote. Our module has the following components: (1) a graphical user interface component that combines a color liquid crystal display (LCD) and 5-way buttons, (2) a power meter component that is reconfigurable for attaching various low-power devices, and (3) a data logger component that is interfaced to a removable secure digital (SD) or multimedia memory card (MMC). The module dimensions are 34times58times12 mm. This paper describes the hardware and software design and experiences while developing and using the device. The device is evaluated by comparing its parameters and functionality to laptop and PDA solutions. We conclude that SeeMote is preferred for certain WSNs, such as very large scale, difficult to reach, and wearable WSNs. We also present several applications that use the LCD module, such as the portable frequency spectrum analyzer and remote sensory data display device.