Although touted as a revolutionary technology with a wide scope of application, the actual design and implementation of full, end-to-end wireless sensor networks (WSNs) has rarely been demonstrated. One of the primary factors holding back the field is that the capabilities of WSNs and realistic specifications of WSN applications are not well understood. Much research has been devoted to specific hardware, software, or algorithmic components of these networks with very little work having been done on full system implementation for real-world problems. The multitude of WSN components that have been developed result from different tradeoffs made among the parameters governing WSN systems. This paper introduces and analyzes these governing parameters and how tradeoffs are made among them. Ultimately, a matching metric presented helps WSN designers use specifications on these parameters to find and integrate appropriate WSN components for implementing real-world WSN solutions.
In case studies of recent MOUT failures, one of the most widely given reports from soldiers in the field was that MOUT environments are extremely confusing and complex. This confusion manifests itself by creating soldier-level difficulties in determining appropriate and operationally consistent responses to various fast paced and close range changes in the mission environment. Lack of commander-level situational awareness and robust commander-to-soldier communications cripple mission effectiveness. Furthermore, current military technologies are mostly unsuitable for urban terrain since they are generally intended for long range and coarse-grained operations which are uncommon in MOUT. The emerging technology of wireless sensor networks has potential to solve many current MOUT issues, and will be a vital part of the network-centric warfare discussed in relation to the Future Combat System (FCS). This paper will discuss technological enhancements and impacts to MOUT based on wireless sensor networks with specific emphasis on low-cost and disposable sensor system opportunities.
The system level hardware architecture of individual nodes in a wireless distributed sensor network has not received adequate attention. A large portion of the development work in wireless sensor networks has been devoted to the networking layer or the network communications, but considering the tight integration required between the hardware and software on each node can result in major benefits in power, performance, and usability as well. A novel hardware architecture based on the concept of task specific modular computing provides both the high flexibility and power efficiency required for effective distributed sensing solutions. A comparative power analysis with a traditional, centralized architecture gives a justifying motivation for pursuing the modular architecture. Finally, three decentralized module self-control mechanisms developed to minimize total system power will be presented and explained in detail.
The recent war on terrorism and increased urban warfare has been a major catalysis for increased interest in the development of disposable unattended wireless ground sensors. While the application of these sensors to hostile domains has been generally governed by specific tasks, this research explores a unique paradigm capitalizing on the fundamental functionality related to sensor systems. This functionality includes a sensors ability to Sense - multi-modal sensing of environmental events, Decide - smart analysis of sensor data, Act - response to environmental events, and Communication - internal to system and external to humans (SDAC). The main concept behind SDAC sensor systems is to integrate the hardware, software, and networking to generate 'knowledge and not just data'. This research explores the usage of wireless SDAC units to collectively make up a sensor system capable of persistent, adaptive, and autonomous behavior. These systems are base on the evaluation of scenarios and existing systems covering various domains. This paper presents a promising view of sensor network characteristics, which will eventually yield smart (intelligent collectives) network arrays of SDAC sensing units generally applicable to multiple related domains. This paper will also discuss and evaluate the demonstration system developed to test the concepts related to SDAC systems.
KEYWORDS: Sensor networks, Sensors, Data acquisition, Wireless communications, Chemistry, Operating systems, Signal processing, Digital signal processing, Prototyping, Lithium
The Hybrid Emergency Radiation Detection (HERD) system is a rapidly deployable ad-hoc wireless sensor network for monitoring the radiation hazard associated with a radiation release. The system is designed for low power, small size, low cost, and rapid deployment in order to provide early notification and minimize exposure. The many design tradeoffs, decisions, and challenges in the implementation of this wireless sensor network design will be presented and compared to the commercial systems available. Our research in a scaleable modular architectural highlights the need and implementation of a system level approach that provides flexibility and adaptability for a variety of applications. This approach seeks to minimize power, provide mission specific specialization, and provide the capability to upgrade the system with the most recent technology advancements by encapsulation and modularity. The implementation of a low power, widely available Real Time Operating System (RTOS) for multitasking with an improvement in code maintenance, portability, and reuse will be presented. Finally future design enhancements technology trends affecting wireless sensor networks will be presented.
Wireless sensor networks allow detailed sensing of otherwise
unknown and inaccessible environments. While it would be
beneficial to include cameras in a wireless sensor network because
images are so rich in information, the power cost of transmitting
an image across the wireless network can dramatically shorten the
lifespan of the sensors. This paper investigates various
compression techniques and what the cost of these algorithms would
be to the lifespan of the sensor nodes. We further describe a new
paradigm for cameras and wireless networks. Rather than focusing
on transmitting images across the network, we show how an image
can be processed locally for key features using simple detectors.
Contrasted with traditional event detection systems that trigger a
an image capture, this enables a new class of sensors which uses a
low power imaging sensor to detect a variety of visual cues.
KEYWORDS: Sensors, Intelligence systems, Analytical research, Data fusion, Data modeling, Data analysis, Control systems, Sensing systems, Sensor technology, Intelligent sensor systems
The wireless intelligent monitoring and analysis systems is a proof-of-concept directed at discovering solution(s) for
providing decentralized intelligent data analysis and control for distributed containers equipped with wireless sensing
units. The objective was to embed smart behavior directly within each wireless sensor container, through the
incorporation of agent technology into each sensor suite. This approach provides intelligent directed fusion of data based
on a social model of teaming behavior. This system demonstrates intelligent sensor behavior that converts raw sensor
data into group knowledge to better understand the integrity of the complete container environment. The emergent team
behavior is achieved with lightweight software agents that analyze sensor data based on their current behavior mode.
When the system starts-up or is reconfigured the agents self-organize into virtual random teams based on the
leader/member/lonely paradigm. The team leader collects sensor data from their members and investigates all abnormal
situations to determine the legitimacy of high sensor readings. The team leaders flag critical situation and report this
knowledge back to the user via a collection of base stations. This research provides insight into the integration issues and
concerns associated with integrating multi-disciplinary fields of software agents, artificial life and autonomous sensor
behavior into a complete system.
This research is concerned with the design, development and implementation of a unique reaction-based multi-agent architecture (REAGERE) to integrate and control a manufacturing domain, by combining concepts from distributed problem solving and multi-agent systems. This architecture represents an emerging concept of reifying the parts, equipment, and software packages of the domain as individual agent entities. This research also improves on earlier top- down automated manufacturing systems, that suffered from lack of flexibility, upgradability, overhead difficulties, and performance problems when presented with the uncertainty and dynamics of modern competitive environments. The versatility of the domain is enhanced with the independent development of the agents and the object-oriented events that permit the agents to communicate through the underlying blackboard architecture BB1. This bottom-up concept permits the architecture's integration to rely on the agents' interactions and their perceptions of the current environmental problem(s). Hence the control and coordination of the architecture are adaptable to the agents' reactions to dynamic situations. REAGERE was applied to a simulated predefined automated manufacturing domain for the purpose of controlling and coordinating the internal processes of this domain.
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