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In earlier articles on intelligent sensor design, we saw how valuable they can be to both end users and those who manufacture and sell them. It’s now time to delve more deeply into what it takes to make intelligent sensors work.   The first step in that journey is to develop a solid, intuitive understanding of the principles of digital signal processing(DSP). Unlike many introductory DSP articles and texts, the focus here will be on presenting and using the important concepts rather than deriving them, for the simple reason that addressing the subject in depth is a book-sized, not a chapter-sized, project.

Earlier in this series, we touched on one problem that can arise when sampling an analog signal, namely the problem of aliasing. There are three other issues with signal sampling to which we now turn our attention: digitization effects, finite register length effects, and oversampling. So far, weve assumed that all of the signals were measuring are continuous analog values; i.e., our measurements are completely accurate. Even in the cases in which we have noise, the underlying assumption is that the measurement itself, for example the noisy sensor output voltage, is known precisely.

We’re all familiar with the general idea of a filter: it removes something that we don’t want from something we do want. Coffee filters that pass the liquid coffee but retain the grounds or air filters that pass clean air but trap the dust and other pollutants are two common examples of mechanical filters in everyday life. That same concept can be applied to noisy electrical signals to pass through the “true” signal of interest while blocking the undesirable noise signal. Looking at Figure 2.5c below, imagine for a moment that the signal of interest is in the lower-frequency region and that the noise signal is in the higher-frequency region. Ideally, we’d like to be able to get rid of that high-frequency noise, leaving just the signal component that we want.

When Pantelis Georgiou and his fellow biomedical engineers at Imperial College London decided to design an intelligent insulin pump for diabetes patients, they started at the source. "We asked ourselves, what does a pancreas do to control blood glucose?" Georgiou recalls. The answer is pretty well known: The organ relies primarily on two populations of cells—beta cells, to secrete insulin when blood glucose is high, and alpha cells, which release a hormone called glucagon when glucose levels are low. "We simulated them both in microchip form," Georgiou says. This biomimetic approach diverges from today's dominant method of delivering only insulin using a relatively simple control system.

In then the past few years we have seen multiprocessing systems become more mainstream, in fact most modern personal computer CPUs now feature symmetric multiprocessing systems (SMP), where multiple instantiations of the same processor share the processing burden of the applications running on the PC. While SMPs are quite common today, we typically have not seen a shift towards multiprocessing in embedded computing. However, a new type of embedded design technique gives engineers the freedom to intelligently distribute processing functions across a digital subsystem. This article will look at an example of the distributed processing technique using Cypress Semiconductor's PSoC 3 and PSoC 5 architectures, which consist of a main CPU (in this case an 8051 or ARM Cortex M3), a DMA engine, and array of Universal Digital Blocks (UDB).

French service robotics company Robosoft has introduced a robot called Kompaï designed to assist elderly and disabled people and others who need special care. The mobile robot talks, understands speech, and can navigate autonomously. It reminds people of meetings, keeps track of shopping lists, plays music, and works as a videoconference system for users to talk with their doctors, for example. The video below is pretty awesome. It shows a senior at Broca Hospital, in Paris, interacting with the robot after receiving only a few minutes of training. The man asks the robot about the time, date, and whether he has any appointments that day; Kompaï gives answers in a computerized voice.