Real-time embedded systems for safety-critical applications have to introduce fault tolerance mechanisms in order to cope with hardware and software errors. Fault tolerance is usually applied by means of redundancy and diversity. Redundant hardware implies the establishment of a distributed system executing a set of fault tolerance strategies by software, and may also employ some form of diversity, by using different variants or versions for the same processing. This paper describes our approach to introduce fault tolerance in distributed embedded systems applications, using aspect-oriented programming (AOP). A real-time operating system supporting middleware thread communication was integrated to a fault tolerant framework. The introduction of fault tolerance in the system is performed by AOP at the application thread level. The advantages of this approach include higher modularization, less efforts for legacy systems evolution and better configurability for testing and product line development. This work has been tested and evaluated successfully in several fault tolerant configurations and presented no significant performance or memory footprint costs.
The uniqueness of microelectromechanical system (MEMS) devices, with their multiphysics characteristics, presents some limitations to the borrowed test methods from traditional integrated circuits (IC) manufacturing. Although some improvements have been performed, this specific area still lags behind when compared to the design and manufacturing competencies developed over the last decades by the IC industry. A complete digital solution for fast testing and characterization of inertial sensors with built-in actuation mechanisms is presented in this paper, with a fast, full-wafer test as a leading ambition. The full electrical approach and flexibility of modern hardware design technologies allow a fast adaptation for other physical domains with minimum effort. The digital system encloses a processor and the tailored signal acquisition, processing, control, and actuation hardware control modules, capable of the structure position and response analysis when subjected to controlled actuation signals in real time. The hardware performance, together with the simplicity of the sequential programming on a processor, results in a flexible and powerful tool to evaluate the newest and fastest control algorithms. The system enables measurement of resonant frequency (Fr), quality factor (Q), and pull-in voltage (Vpi) within 1.5 s with repeatability better than 5 ppt (parts per thousand). A full-wafer with 420 devices under test (DUTs) has been evaluated detecting the faulty devices and providing important design specification feedback to the designers.
There is a growing demand for low cost, very low power and reduced size monitoring systems with wireless communications, to be used in different kinds of industrial environments. In several countries waste separation and recycling is a major issue. Consequently, the number of recycling spots has been steadily increasing. In order to ensure that recycle bins are properly maintained, several monitoring solutions have been proposed. These still have several limitations, such as requiring wires for power and/or communications and not being able to fit in all existing types of bins. This paper presents WECO, a wireless embedded solution for monitoring the level of the bins located in recycling spots. The proposed system automatically alerts a remote central station when a bin reaches a programmable filling level, thus avoiding the need to spot check if the bin is full and ensuring that the recycling spot is kept clean. The developed prototype required hardware-software co-design and aimed to meet the above mentioned requirements, resorting to the IEEE 802.15.4 protocol for wireless communications between all nodes in the network, each based on a System-On-Chip (SoC) CC2530 from Texas Instruments. Due to its wireless nature, the architecture requires a battery for power supplying the nodes, with a life time of at least six years. The filling level readings of each bin in a recycling spot is made using an ultrasonic sensor. The data collected by the monitoring platform is then sent to the remote central station that processes it in order to optimize routes and establish a scheduled collection of the recycling spots.
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