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This document summarises the results of several research campaigns over thepast seven years. The main connecting theme is the physical layer of widelydeployed sensors in Pervasive Computing domains. In particular, we have focusedon the RF-channel or on ambient audio.  The initial problem from which we started this work was that of distributedadaptive transmit beamforming. We have been looking for a simple method toalign the phases of jointly transmitting nodes (e.g. sensor or IoT nodes). Thealgorithmic solution to this problem was to implement a distributed randomoptimisation method on the participating nodes in which the transmitters andthe receiver follow an iterative question-and-answer scheme. We have been ableto derive sharp asymptotic bounds on the expected optimisation time of anevolutionary random optimiser and presented an asymptotically optimal approach.  One thing that we have learned from the work on these physical layeralgorithms was that the signals we work on are fragile and perceptive tophysical environmental changes. These could be obstacles such as furniture,opened or closed windows or doors as well as movement of individuals. Thisobservation motivated us to view the wireless interface as a sensor forenvironmental changes in Pervasive Computing environments.  Another use of physical layer RF-signals is for security applications.  We are currently working to further push these mentioned directions and novelfields of physical prototyping. In particular, the calculation of mathematicaloperations on the wireless channel at the time of transmission appears tocontain good potential for gains in efficiency for communication andcomputation in Pervasive Computing domains.

Some aspects of physical prototyping in Pervasive Computing