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Sensors technologies – part 2
The direct or indirect use of living cells and their manipulating to acquire specific characteristics has led to the creation of sensors leveraging on living material like bacteria and algae. As an example blue-green algae are being used for sensing the presence of contaminant in marine and fresh water by measuring their density through fluorometers attuned to algae chlorophyll.
Live cells have also been integrated in microfluidic devices to act as “bio-reporters” with the aim of enabling autonomous environment monitoring.
A slightly different situation applies to bio-sensors for interfacing with living beings. Here the evolution is also impressive but there is no silver bullet in sight.
The sensing of activities going on in a living being is complicated by several factors:
- the noise generated by concurrent, although unrelated activities (in a brain there is a flow of electrical/chemical activity related to, e.g., moving an arm that occurs in parallel with hundreds other electrical/chemical activities like seeing, earing, regulating breathing….)
- the distribution of signals over a broad area (staying with the example of moving an arm there are several parts and hundreds/thousands of neurones involved) makes it difficult to pick up the signals at the point of origin. The further away the signal is picked up the more noisy it results.
- the difficulty in keeping the sensing probe in place since the living matter is soft and keeps changing.
- the possible change in the way communications is generate and changes in a living being (the process of learning changes the brain and in turns it changes the neurones involved in a given action/thought and their mutual communications).
Given the present status of knowledge it seems more likely that it will remain impossible to pinpoint the origin of single activities and the evolution in this area is towards a global understanding of the semantics, thus the sensing will generate basically non-specific data and these will have to be processed to derive specific information.
In a way the approach is to the mimic human way of “understanding” another human, by observing the external behaviour rather than by capturing what, internally, led to such behaviour. Clearly, this approach works when the understanding can be derived from “actions” but it does not work when there is a need to capture thoughts (such as the case of creating a symbiotic relation with a paralysed person who can only “think” about an action). In general, the approach of understanding through behaviour observation is best for autonomous systems since it is unlikely that they can get a direct hook into another system. More on this in a future post discussing Communications and Cooperative Support Technologies.
