Jürgo-Sören Preden

The Benefits of Self-Awareness and Attention in Fog and Mist Computing

Self-awareness facilitates a proper assessment of cost-constrained cyber-physical systems, allocating limited resources where they are most needed. Together, situation awareness and attention are key enablers for self-awareness in efficient distributed sensing and computing networks.

Design of Fuzzy Rule-based Classifiers through Granulation and Consolidation

Abstract This paper addresses the issue how to strike a good balance between accuracy and compactness in classification systems - still an important question in machine learning and data mining. The fuzzy rule-based classification approach proposed in current paper exploits the method of rule granulation for error reduction and the method of rule consolidation for complexity reduction. The cooperative nature of those methods - the rules are split in a way that makes efficient rule consolidation feasible and rule consolidation itself is capable of further error reduction - is demonstrated in a number of experiments with nine benchmark classification problems. Further complexity reduction, if necessary, is provided by rule compression.

Location awareness of information agents

This paper discusses the use of generic geospatial agents (provided by agent development environment KRATT) for collecting and processing location aware information. The approach is essentially based on agent-based digital map processing software that is capable of handling raster or vector maps, and maps with different colour schemes, with different packing methods, with different systems of signs, etc. Each application can be configured and reconfigured dynamically. Agents, and the applications that use services provided by agents, are not in one-to-one relationship; one agent can simultaneously work with many applications. Also, an agent may use services from different agents in different situations. The approach is illustrated by pilot applications, such as participatory GIS, tracking of active objects, information collection and navigation in a sensor network with beacons.

Simplified acoustic localization by linear arrays for wireless sensor networks

The application of wireless sensor networks (WSN) for the task of acoustic localization provides great opportunities for distributed cooperative tracking of sound sources in large areas. However WSNs are significantly more limited in terms of computational resources and power than typical computer systems. Therefore the methods applied for acoustic localization in WSN must be optimized for minimal resource consumption. This paper builds on the advances of Steered Response Power with Phase Transform (SRP-PHAT) optimization and proposes a further simplification in terms of additional minimization of the initial search volume. By using several linear microphone arrays we are able to estimate the initial region of sound source and reduce the number of computations by at least one order of magnitude. The results of several experiments on real signals confirm the achieved improvements.

Object detection for military surveillance using distributed multimodal smart sensors

This paper considers an autonomous ground Intelligence, Surveillance and Reconnaissance (ISR) system comprising of multiple distributed, wirelessly communicating smart sensors. The ISR system, in turn, is a part of a larger System of Systems (SoS) consisting of aerial, manned, etc. surveillance systems and information collection centers. The smart sensors of the ISR system perform environment monitoring using different modalities and exchange object detection and identification results to assess the situation and provide other SoS components with this information. In the paper we discuss using acoustic, magnetic and Passive Infrared (PIR) sensor information for target detection and identification. We also propose an approach of distributed acoustic source localization and a method of velocity estimation using PIR data. For sensor communication an asynchronous ad-hoc WSN configuration is proposed. The system is implemented on low power smart sensors utilizing Atmel ATmega128RFA1 processors with integrated 2.4GHz IEEE 802.15.4 compliant radio transceivers.

A two-stage approach to 2D DOA estimation for a compact circular microphone array

Microphone arrays and, specifically, circular arrays have been used for sound source localization and multimedia applications for more than a decade. In recent years the development of compact arrays for implementation in Wireless Sensor Networks (WSN) has risen in popularity. This paper considers a 2D Direction of Arrival (DOA) estimation method for a compact circular array, equipped with additional vertically placed microphones. The proposed method is aimed at reducing the computational cost of DOA estimation for implementation on embedded hardware of WSN smart sensors. The method is compared with a well known localization algorithm of SRP-PHAT and is proven to provide adequate DOA estimates, while being more computationally effective.

Collective acoustic localization in a network of dual channel low power devices

Situation awareness is an important aspect of ubiquitous computer systems, as these systems of systems are highly integrated with the physical world and for successful operation they must maintain high awareness of the environment. Acoustic information is one of the most popular modalities, by which the environment states are estimated. Multi-sensor approaches also provide the possibility for acoustic source localization. This paper considers an acoustic localization system of dual channel smart sensors interconnected through a Wireless Sensor Network (WSN). The low computational power of smart sensor devices requires distribution of localization tasks among WSN nodes. The Initial Search Region Reduction method is used in the WSN to meet this requirement. The system is implemented on smart dust motes utilizing Atmel ATmega128RFA1 processors with integrated 2.4GHz IEEE 802.15.4 compliant radio transceivers. The paper discusses complications, introduced by low power hardware, and reviews conditions of real-time operation.

Self-aware architecture to support partial control of emergent behavior

System of systems comprises interacting, heterogeneous, autonomous components with incomplete information about their inner states, and about the surrounding environment. Many interactions are often not rigorously defined, and change dynamically. System of systems usually exhibits emergent behavior that cannot be predicted by analyzing static properties of the components, and is not always permissible. This paper suggests that the designer can improve systems behavior by substituting (part of) regular interactions with smart mediated interactions that bolster up shared situation awareness of the systems components and thus strengthens systems capability to monitor and partially control its emergent behavior. This paper discusses smart mediated interactions that focus on awareness of temporal features and on estimates of spatial location of the components. Interactions are assembled into proactive middleware that forms a backbone of system of systems.

Communication Area Based Positioning

This paper presents an algorithm for positioning sensor network nodes based on the communication areas of the nodes. The nodes can be positioned either using a small number of anchor nodes or a single location aware mobile node which can determine its location dynamically through external means (e.g. an existing infrastructure, such as GPS). The algorithm does not use any distance or bearing estimations between nodes, but instead the communication areas of anchor nodes are used to determine the position of nodes. The paper presents an overview of the algorithm explaining the main principles of the algorithm. A semi-formal description of the algorithm is given, followed by the description of the simulations. The simulations involved randomly and relatively sparsely distributed nodes in a square area with randomly and more sparsely distributed anchor nodes in the same area. In addition to simulations some tests in a test environment were conducted positioning MICA2 motes and RF ID tags by a mobile location aware platform. The test setup is described and the test results are presented. The paper is concluded by some finalizing remarks and ideas for further research

Situation awareness via Internet of things and in-network data processing

Computing on the edge of the Internet of things comprises among other tasks in-sensor signal processing and performing distributed data fusion and aggregation at network nodes. This poses a challenge to distributed sensor networks of low computing power devices that have to do complex fusion, aggregation and signal processing in situ. One of the difficulties lies in ensuring validity of data collected from heterogeneous sources. Ensuring data validity, for example, the temporal and spatial correctness of data, is crucial for correct in-network data fusion and aggregation. The article considers wireless sensor technology in military domain with the aim of improving situation awareness for military operations. Requirements for contemporary intelligence, surveillance and reconnaissance applications are explored and an experimental wireless sensor network, designed to enhance situation awareness to both in-the-field units and remote intelligence operatives, is described. The sensor nodes have the capability to perform in-sensor signal processing and distributed in-network data aggregation and fusion complying with edge computing paradigm. In-network data processing is supported by service-oriented middleware which facilitates run-time sensor discovery and tasking and ad hoc (re)configuration of the network links. The article describes two experiments demonstrating the ability of the wireless sensor network to meet intelligence, surveillance and reconnaissance requirements. The efficiency of distributed data fusion is evaluated and the importance and effect of establishing data validity is shown.