We report on the use of a sprayable and thermogelating biomaterial (Poloxamer; a.k.a. Pluronic) in optical imaging of pH values, local oxygen and temperature. The material is highly biocompatible and easy to handle. We also show that the material is well permeable to oxygen (thus making it a good choice for use in oxygen sensors), and is stable in liquid solution and at elevated temperature. We demonstrate its applicability in optical sensors for oxygen, pH and temperature. This was accomplished by incorporating appropriate luminescent probes in various kinds of microparticles (which act as hosts for the probes and prevent dye leaching and aggregation), and then dispersing the microparticles in the thermogelating polymer. The resulting sensor gels were deposited on the surface of interest via spraying at temperatures of <20 °C. At these temperatures, the gels adhere well to the target, even on uneven surfaces such as skin, wounds, and bacterial cultures. If temperature is risen to above 25 °C, the gels form a thin and soft but solid sensing layer which, however, can be simply removed from surface of interest by cooling and wiping it off, or by washing with water. Sprayable thermogelating sensors present obvious advantages over other sensors by not causing damage to the surface of interest. In our perception, the sensing materials also have wide further applicability in sensors for other species including clinically relevant gases, enzyme substrates (such as glucose or lactate) and ions.
This article presents the development and validation of an autonomous, gas sensitive microdrone that is capable of estimating the wind vector in real time using only the onboard control unit of the microdrone and performing gas distribution mapping (DM). Two different sampling approaches are suggested to address this problem. On the one hand, a predefined trajectory is used to explore the target area with the microdrone in a real-world gas DM experiment. As an alternative sampling approach, we introduce an adaptive strategy that suggests next sampling points based on an artificial potential field (APF). Initial results in real-world experiments demonstrate the capability of the proposed adaptive sampling strategy for gas DM and its use for gas source localization.
This paper presents a sampling strategy for mobile gas sensors. Sampling points are selected using a modified artificial potential field (APF) approach, which balances multiple criteria to direct sensor measurements towards locations of high mean concentration, high concentration variance and areas for which the uncertainty about the gas distribution model is still large. By selecting in each step the most often suggested close-by measurement location, the proposed approach introduces a locality constraint that allows planning suitable paths for mobile gas sensors. Initial results in simulation and in real-world experiments with a gas-sensitive micro-drone demonstrate the suitability of the proposed sampling strategy for gas distribution mapping and its use for gas source localization.
BAM Federal Institute for Materials Research and Testing, in cooperation with the AirRobot GmbH & Co. KG company, has developed a flying remote-controlled measuring system. The system is capable of operating in a variety of scenarios of gas emissions, e.g. exhaust gas from chimneys, flue gas in a fire, gas emissions in the case of an accident of chemical or hazardous goods or in the case of a terrorist act involving toxic gases. Thus it can measure the gas concentration in the immediate vicinity of the object which causes the emission. A further stage of extension is to enhance the system for plume tracking and identification of sources of hazardous gases.