4th International Electronic Conference on Sensors and Applications
S2: Smart Sensing Systems and Structures
Dr. Dirk Lehmhus, ISIS Sensorial Materials Scientific Centre, University of Bremen, Germany
Dr. Stefan Bosse, Department of Computer Science, Workgroup Robotics, University of Bremen, Bremen, Germany
Trends emerging in engineering and micro-system applications such as the development of sensorial materials show a growing demand for distributed autonomous computing in sensor networks consisting of miniaturized low-power smart sensors embedded in technical structures. A Sensor Network is composed of nodes capable of sensor processing and communication. Smart Systems are composed of more complex networks (and networks of networks) differing significantly in computational power and available resources. They provide higher level information processing that maps the raw sensor data to condensed information. They can provide, for example, Internet connectivity of perceptive systems (body area networks...). These smart systems unite the traditionally separated sensing, aggregation, and application levels, offering a more unified design approach and more generic and unified architectures. Smart systems glue software and hardware components to an extended operational unit.
Smart can be defined on different operational and processing levels and having different goals in mind. One aspect is the adaptivity and reliability in the presence of sensor, communication, node, and network failures that should not compromise the trust and quality of the computed information, for example, the output of a Structural Health Monitoring System (SHM). A Smart System can be considered on node, network, and network of network level. Another aspect of "smartness" is information processing with inaccurate or incomplete models (mechanical, technical, physical) requiring machine learning approaches, either supervised with training at design-time or unsupervised based on reward learning at run-time.
Growing system complexity requires an increase in autonomy of distributed data processing systems, addressed, for example, by the deployment of mobile multi-agent systems carrying and processing information. Self-organizing systems are one major approach to solve complex tasks by decomposing them into smaller and simpler task performed by a large group of individuals.
Smart "Functional" Structures extend classical perceptive systems with actuators responding to changes in the environment or load conditions in real-time, enabling Reactive Perceptive Systems.
Topics included but not limited to are:
- Software engineering for sensing applications and sensor clouds
- Data mining in sensing applications
- Autonomous computing systems
- Multi-agent systems and intelligent computing
- Machine learning supporting sensing applications
- Ubiquitous smart systems and applications
- Sensor cloud, cluster and grid computing
- Internet of Things
- Human-computer, human-sensing, and human-machine interaction
- Machine-to-Machine (M2M) networks
- Service-orientated information processing and computing
- Reliable and fault-tolerant system design and algorithms
- Platform design and architectures
- Active perceptive systems coupling sensing + actuation including robotic systems