Environmental Engineering Applications of Electronic Nose Systems Based on MOX Gas Sensors

Nowadays, the electronic nose (e-nose) has gained a huge amount of attention due to its ability to detect and differentiate mixtures of various gases and odors using a limited number of sensors. Its applications in the environmental fields include analysis of the parameters for environmental control, process control, and confirming the efficiency of the odor-control systems. The e-nose has been developed by mimicking the olfactory system of mammals. This paper investigates e-noses and their sensors for the detection of environmental contaminants. Among different types of gas chemical sensors, metal oxide semiconductor sensors (MOXs) can be used for the detection of volatile compounds in air at ppm and sub-ppm levels. In this regard, the advantages and disadvantages of MOX sensors and the solutions to solve the problems arising upon these sensors' applications are addressed, and the research works in the field of environmental contamination monitoring are overviewed. These studies have revealed the suitability of e-noses for most of the reported applications, especially when the tools were specifically developed for that application, e.g., in the facilities of water and wastewater management systems. As a general rule, the literature review discusses the aspects related to various applications as well as the development of effective solutions. However, the main limitation in the expansion of the use of e-noses as an environmental monitoring tool is their complexity and lack of specific standards, which can be corrected through appropriate data processing methods applications.

Insect-machine hybrid robot

Recently, insect-machine hybrid robots have been developed that incorporate insects into robots or incorporate machines into insects. Most previous studies were motivated to use the function of insects for robots, but this technology can also prove to be useful as an experimental tool for neuroethology. We reviewed hybrid robots in terms of the closed-loop between an insect, a robot, and the real environment. The incorporated biological components provided the robot sensory signals that were received by the insects and the adaptive functions of the brain. The incorporated artificial components permitted us to understand the biological system by controlling insect behavior. Hybrid robots thus extend the roles of mobile robot experiments in neuroethology for both model evaluation and brain function analysis.

Dropping Counter: A Detection Algorithm for Identifying Odour-Evoked Responses from Noisy Electroantennograms Measured by a Flying Robot

The electroantennogram (EAG) is a technique used for measuring electrical signals from the antenna of an insect. Its rapid response time, quick recovery speed, and high sensitivity make it suitable for odour-tracking tasks employing mobile robots. However, its application to flying robots has not been extensively studied owing to the electrical and mechanical noises generated. In this study, we investigated the characteristics of the EAG mounted on a tethered flying quadcopter and developed a special counter-based algorithm for detecting the odour-generated responses. As the EAG response is negative, the algorithm creates a window and compares the values inside it. Once a value is smaller than the first one, the counter will increase by one and finally turns the whole signal into a clearer odour stimulated result. By experimental evaluation, the new algorithm gives a higher cross-correlation coefficient when compared with the fixed-threshold method. The result shows that the accuracy of this novel algorithm for recognising odour-evoked EAG signals from noise exceeds that of the traditional method; furthermore, the use of insect antennae as odour sensors for flying robots is demonstrated to be feasible.

Target Representation on an Autonomous Vehicle with Low-Level Sensors

How can low-level autonomous robots with only very simple sensor systems be endowed with cognitive capabilities? Specifically, we consider a system that uses seven infrared sensors and five microphones to avoid obstacles and acquire sound targets. The cognitive abilities of the vehicle consist of representing the direction in which a sound source lies. This representation supports target detection, estimation of target direction, selection of one out of multiple-detected targets, storage of target direction in short-term memory, continuous updating of memory, and deletion of memorized target information after a characteristic delay. We show that the dynamic approach (attractor dynamics) employed to control the motion of the robot can be extended to the level of representation by using dynamic neural fields to interpolate sensory information. We show how the system stabilizes decisions in the presence of multivalue sensorial information and activates and deactivates memory. Smooth integration of this target representation with target acquisition, in the form of phonotaxis, and obstacle avoidance is demonstrated.

Bioinspired algorithm for autonomous sensor-driven guidance in turbulent chemical plumes

We designed and implemented a control algorithm for sensor-mediated chemical plume tracking in a turbulent flow environment. In our design, we focused on development of a signal processing strategy capable of replicating behavioral responses of actively tracking blue crabs (Callinectes sapidus) to chemical stimuli. The control algorithm is evaluated in a hardware platform that allows motion in two directions (i.e. forward-back and left-right). The geometric arrangement of the sensor array is inspired by the location of blue crab sensor populations. Upstream motion is induced by a binary response to supra-threshold spikes of concentration, and cross-stream steering is controlled by contrast between bilaterally-separated sensors. Like animal strategies, the developed control algorithm is dynamic. This property allows the algorithm to function effectively in the highly irregular turbulent environment and produces adaptive adjustments of motion to minimize the distance to the source of a plume. Tracking trials indicate that roughly 80% of the tracks successfully stop near the plume source location. Both success rate and movement patterns of the tracker compare favorably to that of blue crabs searching for odorant plume sources, thus suggesting that our sensory-mediated behavior hypothesis are generally accurate and that the associated tracking mechanisms may be successfully implemented in hardware.

Long-term and room temperature operable bioactuator powered by insect dorsal vessel tissue

We present a bioactuator powered by insect dorsal vessel tissue which can work for a long time at room temperature without maintenance. Previously reported bioactuators which exploit contracting ability of mammalian heart muscle cell have required precise environmental control to keep the cell alive and contracting. To overcome this problem, we propose a bioactuator using dorsal vessel tissue. The insect tissue which can grow at room temperature is generally robust over a range of culture conditions compared to mammalian tissues and cells. First, we confirm that a dorsal vessel tissue of lepidoptera larva Ctenoplusia agnata contracts spontaneously for at least 30 days without medium replacement at 25 degrees C. Using the dorsal vessel tissue cultured under the same conditions, we succeed in driving micropillars 100 microm in diameter and 1000 microm in height for more than 90 days. The strongest displacement of the micropillar top occurs on the 42(nd) day and is 23 microm. Based on these results, the contracting force is roughly estimated as 4.7 microN which is larger than that by a few mammalian cardiomyocytes (3.4 microN). Definite displacements of more than 10 microm are observed for 58 days from the 15(th) to the 72(nd) days. The number of life cycles can be roughly calculated as 7.5 x 10(5) times for the average frequency of about 0.15 Hz, which is no less than that of conventional mechanical actuators. These results suggest that the insect dorsal vessel tissue is a more promising material for bioactuators used at room temperature than other biological cell-based materials.

Robot Odor Localization: A Taxonomy and Survey

Robotic odor localization has become a prominent research area in recent years. It promises many valuable practical applications, and contributes to the knowledge of biological odor localization, which has in many cases been the source of inspiration. There have been a diversity of approaches, implemented in both simulated and practical experiments, with a wide variety of platforms, and in a number of environments. This article presents a survey of the existing methods, which have been organized into taxonomic classifications. This provides a framework in which to evaluate the methods, view how they relate to each other, and make qualitative comparisons. The methods are grouped at the highest level by environmental conditions, and then by the localization method which in most cases is closely associated with the type of sensors used.

Insect-Controlled Robot – Evaluation of Adaptation Ability –

Insects can adapt to various environments and perform adaptive behaviors with their simple nervous system. Understanding of the mechanisms underlying these adaptive behaviors has been expected to lead to novel control systems in robotics. In this study, we proposed and developed a robot controlled by an insect in order to evaluate the adaptability of insects. This robot reproduced the behavior of a male silkmoth (Bombyx mori) tethered on it with high precision, and was successful in reproducing the pheromone-oriented behavior that is an adaptive behavior of the male silkmoth. When we changed the forward motor gain of the robot, its speed changed based on the manipulation. However, the manipulated robot performed the same ability for the sex-pheromone orientation as existed before the manipulation. This implied that the programmed behavior pattern of the pheromone-oriented behavior was robust and important for successful orientation, which did not depend on the speed of movement. This robot exhibits a new method to manipulate interaction between the body and the environment and is expected to prove useful as a new experimental platform for analyzing adaptability.

Improvement of signal-to-noise ratio in electroantennogram responses using multiple insect antennae

Using an array of insect antennae connected in series or in parallel, electroantennogram (EAG) responses and noise levels were investigated in an attempt to improve signal-to-noise (S/N) ratio and sensitivity. Both the EAG response amplitude and noise level increased when the antennae of male Helicoverpa zea (Lepidoptera: Noctuidae) were connected in series. Due to lower relative increase in noise level than EAG amplitude as the number of antennae increased, the S/N ratio was also significantly improved by the serial connection. As a result the sensitivity of EAG was improved by the serial connection, which showed ca. ten-fold improvement in the threshold detection levels compared with a single antenna when four antennae were connected in series. In contrast to the serial connection, there were no differences in EAG amplitudes and overall noise levels when different numbers of antennae were connected in parallel. When only large-amplitude noise was taken into account, however, the S/N ratio was somewhat improved by the parallel connection. The frequency of overall noise remained at the same level both in the serial and in the parallel connection. However, the frequency of the large-amplitude noise increased in serial connection but decreased in parallel connection. The present study clearly indicates that both the sensitivity and S/N ratio of the EAG biosensor could be significantly improved by using the multiple antennal connections.

Behavioral observations and computer simulations of blue crab movement to a chemical source in a controlled turbulent flow

The behavior of crabs tracking odor in turbulent chemical plumes was compared to the performance of computer simulations of search behavior operating in similar chemical signal environments. The movement of blue crabs(Callinectes sapidus) towards a source of food odor was studied in controlled flow conditions in a flume. The evolving chemical stimulus field of a similar chemical source in an equivalent flow environment was captured by recording concentration patterns of a fluorescent tracer. Hypotheses about the sensory mechanisms employed by the crabs were tested by computer simulation using the recorded fluorescence as the stimulus. The results demonstrate that a simple model combining chemotropotaxis (simultaneous, spatial comparisons of chemical signals) and odor-stimulated upstream movement (rheotaxis) is sufficient to explain the efficient movements towards the source displayed by foraging crabs. Spatial integration around each sensor improves performance significantly, but the number of sensors does not have a large impact on performance. The weighting of information from chemical versus flow signals can substantially change simulation performance, resulting in more or less congruence between the behavior of simulations and that of crabs, which suggests the general importance of both sources of information for successful odor-guided navigation.