Search Results (39)

In recent years, the demand for mobile robots to perform odor source localization tasks in dangerous environments has been increasing, and this technology has gradually become a focus of research. However, existing bio-inspired algorithms still have many limitations in real applications. Therefore, we attempt to design a moth-inspired algorithm integrated with a fuzzy control mechanism to enhance the robot’s ability to track odor sources in environments with dense obstacles. The goal is to improve the accuracy and efficiency of localization. Through multiple sets of simulation and real environment experiments, we observed that this algorithm achieved significant improvements in multiple indicators, including task success rate, search efficiency, and path planning quality. Compared with the traditional moth algorithm, its stability and adaptability in complex scenarios are also outstanding. Full article

Industrial odour is a common pollution concern raised with local regulatory authorities, with communities citing impacts to their mental health and wellbeing. We performed a systematic review to determine if industrial odours are associated with psychosocial wellbeing in nearby communities. PubMed, Medline, PsycINFO, and Web of Science were searched for peer-reviewed articles published between 2003 and 2023, assessing associations between industrial odour and psychosocial wellbeing (mental health or quality of life). Critical appraisal of the studies was conducted using JBI’s assessment tools. We undertook a narrative synthesis of results. After screening, 13 articles met the inclusion criteria: 11 cross-sectional and 2 longitudinal studies. Sample sizes ranged from 23 to 25,236 participants. Odour exposure was assessed through self-reported measures (intensity, annoyance) and objective measures (proximity to source, odorous chemical concentration). Psychosocial health outcomes included stress, psychological distress, quality of life, depression and anxiety. Of the 13 studies, 11 identified an association between odour exposure and poorer psychosocial wellbeing, with the strongest evidence relating to quality of life. However, the critical appraisal identified quality issues with most studies. The findings suggest that industrial odours may be associated with poorer psychosocial wellbeing for nearby residents, particularly in terms of quality of life. Future research using consistent objective and subjective measures of odour exposure, and prospective data collection, would strengthen the quality of the evidence. Full article

Cognitive Odor Source Localization (OSL) strategies are reliable search strategies for turbulent environments, where chemical cues are sparse and intermittent. These methods estimate a probabilistic belief over the source location using Bayesian inference and guide the searching movement by evaluating expected entropy reduction at candidate new positions. By maximizing expected information gain, agents make informed decisions rather than simply reacting to sensor readings. However, computing entropy reductions is computationally expensive, making real-time implementation challenging for resource-constrained platforms. Interestingly, search trajectories produced by cognitive algorithms often resemble those of small insects, suggesting that informative movement patterns might be replicated using simpler, bio-inspired searching strategies. This work investigates that possibility by analysing spatial distribution of entropy reductions across the entire search area. Rather than focusing on searching algorithms and local decisions, the analysis maps information gain over the full environment, identifying consistent high-gain regions that may serve as navigational cues. Results show that these regions often emerge near the source and along plume borders and that expected entropy reduction is strongly influenced by prior belief shape and sensor observations. This global perspective enables identification of spatial patterns and high-gain regions that remain hidden when analysis is restricted to local neighborhoods. These insights enable synthesis of hybrid search strategies that preserve cognitive effectiveness while significantly reducing computational cost. Full article

Precise odor source localization in turbulent and sparse environments plays a vital role in enabling robotic systems for hazardous chemical monitoring and effective disaster response. To address this, we propose Cooperative Gravitational-Rényi Infotaxis (CGRInfotaxis), a distributed decision-optimization framework that combines multi-agent collaboration with hybrid cognitive strategy to improve search efficiency and robustness. The method integrates a gravitational potential field for rapid source convergence and Rényi divergence-based probabilistic exploration to handle sparse detections, dynamically balanced via a regulation factor. Particle filtering optimizes posterior probability estimation to autonomously refine search areas while preserving computational efficiency, alongside a distributed interactive-optimization mechanism for real-time decision updates through agent cooperation. The algorithm’s performance is evaluated in scenarios with fixed and randomized odor source locations, as well as with varying numbers of agents. Results demonstrate that CGRInfotaxis achieves a near-100% success rate with high consistency across diverse conditions, outperforming existing methods in stability and adaptability. Increasing the number of agents further enhances search efficiency without compromising reliability. These findings suggest that CGRInfotaxis significantly advances multi-agent odor source localization in turbulent, sparse environments, offering practical utility for real-world applications. Full article

Odor source localization (OSL) technology allows autonomous agents like mobile robots to localize a target odor source in an unknown environment. This is achieved by an OSL navigation algorithm that processes an agent’s sensor readings to calculate action commands to guide the robot to locate the odor source. Compared to traditional ‘olfaction-only’ OSL algorithms, our proposed OSL algorithm integrates vision and olfaction sensor modalities to localize odor sources even if olfaction sensing is disrupted by non-unidirectional airflow or vision sensing is impaired by environmental complexities. The algorithm leverages the zero-shot multi-modal reasoning capabilities of large language models (LLMs), negating the requirement of manual knowledge encoding or custom-trained supervised learning models. A key feature of the proposed algorithm is the ‘High-level Reasoning’ module, which encodes the olfaction and vision sensor data into a multi-modal prompt and instructs the LLM to employ a hierarchical reasoning process to select an appropriate high-level navigation behavior. Subsequently, the ‘Low-level Action’ module translates the selected high-level navigation behavior into low-level action commands that can be executed by the mobile robot. To validate our algorithm, we implemented it on a mobile robot in a real-world environment with non-unidirectional airflow environments and obstacles to mimic a complex, practical search environment. We compared the performance of our proposed algorithm to single-sensory-modality-based ‘olfaction-only’ and ‘vision-only’ navigation algorithms, and a supervised learning-based ‘vision and olfaction fusion’ (Fusion) navigation algorithm. The experimental results show that the proposed LLM-based algorithm outperformed the other algorithms in terms of success rates and average search times in both unidirectional and non-unidirectional airflow environments. Full article

The Andean–Patagonian forests of South America offer a great variety of wild edible mushrooms, many with ancestral use and others linked to new mycogastronomic offers. However, their sensory properties and detailed characterizations have not yet been deeply explored and described, nor have their alterations due to cold storage. The aims of this work were to perform a sensory characterization through a trained panel evaluation, perform target volatile compounds analysis and evaluate post-harvest preservation methods effects on nine species of wild edible mushrooms with different trophic habits (Cortinarius magellanicus, Panus dusenii, Fistulina antarctica, F. endoxantha, Gloeosoma vitellinum, Grifola gargal, Lepista nuda, Ramaria patagonica, and Cyttaria hariotii). The sensory description of dehydrated specimens through quantitative descriptive analysis showed that panelists were a significant source of variation; F. antarctica and R. patagonica registered distinct sweet flavor/spice odor and wood/sweet flavor, respectively, and different textures. Refrigeration produced a rapid loss of sensory characteristics, whereas freezer conservation satisfactorily maintained the characteristics in F. anctartica, R. patagonica, G. vitellinum, and C. hariotti for at least four months. A total of 60 target volatile organic compounds were detected, corresponding to grass, mushroom, alkane, and pungent odors in F. anctartica, R. patagonica, and G. vitellinum. The detailed sensory characterization and post-harvest conservation options of these novel products constitute crucial information to promote their sustainable use and local development through innovative activities linked to tourism, such as mushroom gastronomy and mycotourism. Full article

The visualization of the spatial distributions of gases from various sources is essential to understanding the composition, localization, and behavior of these gases. In this study, an inkjet-printed localized surface plasmon resonance (LSPR) subpixel gas sensor array was developed to visualize the spatial distributions of gases and to differentiate between acetic acid, geraniol, pentadecane, and cis-jasmone. The sensor array, which integrates gold nanoparticles (AuNPs), silver nanoparticles (AgNPs), and fluorescent pigments, was positioned 3 cm above the gas source. Hyperspectral imaging was used to capture the LSPR spectra across the sensor array, and these spectra were then used to construct gas information matrices. Principal component analysis (PCA) enabled effective classification of the gases and localization of their sources based on observed spectral differences. Heat maps that visualized the gas concentrations were generated using the mean squared error (MSE) between the sensor responses and reference spectra. The array identified and visualized the four gas sources successfully, thus demonstrating its potential for gas localization and detection applications. The study highlights a straightforward, cost-effective approach to gas sensing and visualization, and in future work, we intend to refine the sensor fabrication process and enhance the detection of complex gas mixtures. Full article

In this study, we implemented a compact wind direction sensor on a palm-sized quadcopter to achieve wind source localization (WSL). We designed an anemotaxis algorithm based on the sensor data and experimentally validated its efficacy. Anemotaxis refers to the strategy of moving upwind based on information on the wind direction, which is essential for tracing odors propagating through the air. Despite the limited research on quadcopter systems achieving WSL directly through environmental wind measurement sensors, debate remains regarding the relationship between sensor placement and the anemotaxis algorithm. Therefore, we experimentally investigated the placement of a wind direction sensor capable of estimating wind source direction even when propellers are rotating. Our findings demonstrated that placing the sensor 50 mm away from the enclosure of the quadcopter allowed accurate wind direction measurement without being affected by wake disturbances. Additionally, we constructed an anemotaxis algorithm based on wind direction and speed data, which we integrated into the quadcopter system. We confirmed the ability of the quadcopter to execute anemotaxis behavior and achieve WSL irrespective of environmental wind strength through wind source localization experiments. Full article

Aphidius gifuensis is the dominant parasitic natural enemy of aphids. Elucidating the molecular mechanism of host recognition of A. gifuensis would improve its biological control effect. Chemosensory proteins (CSPs) play a crucial role in insect olfactory systems and are mainly involved in host localization. In this study, a total of nine CSPs of A. gifuensis with complete open reading frames were identified based on antennal transcriptome data. Phylogenetic analysis revealed that AgifCSPs were mainly clustered into three subgroups (AgifCSP1/2/7/8, AgifCSP3/9, and AgifCSP4/5/6). AgifCSP2/5 showed high expression in the antennae of both sexes. Moreover, AgifCSP5 was found to be specifically expressed in the antennae. In addition, fluorescent binding assays revealed that AifCSP5 had greater affinities for 7 of 32 volatile odor molecules from various sources. Molecular docking and site-directed mutagenesis results revealed that the residue at which AgifCSP5 binds to these seven plant volatiles is Tyr75. Behavior tests further confirmed that trans-2-nonenal, one of the seven active volatiles in the ligand binding test, significantly attracted female adults at a relatively low concentration of 10 mg/mL. In conclusion, AgifCSP5 may be involved in locating aphid-infested crops from long distances by detecting and binding trans-2-nonenal. These findings provide a theoretical foundation for further understanding the olfactory recognition mechanisms and indirect aphid localization behavior of A. gifuensis from long distances by first identifying the host plant of aphids. Full article

Robotic odor source localization (OSL) is a technology that enables mobile robots or autonomous vehicles to find an odor source in unknown environments. An effective navigation algorithm that guides the robot to approach the odor source is the key to successfully locating the odor source. While traditional OSL approaches primarily utilize an olfaction-only strategy, guiding robots to find the odor source by tracing emitted odor plumes, our work introduces a fusion navigation algorithm that combines both vision and olfaction-based techniques. This hybrid approach addresses challenges such as turbulent airflow, which disrupts olfaction sensing, and physical obstacles inside the search area, which may impede vision detection. In this work, we propose a hierarchical control mechanism that dynamically shifts the robot’s search behavior among four strategies: crosswind maneuver, Obstacle-Avoid Navigation, Vision-Based Navigation, and Olfaction-Based Navigation. Our methodology includes a custom-trained deep-learning model for visual target detection and a moth-inspired algorithm for Olfaction-Based Navigation. To assess the effectiveness of our approach, we implemented the proposed algorithm on a mobile robot in a search environment with obstacles. Experimental results demonstrate that our Vision and Olfaction Fusion algorithm significantly outperforms vision-only and olfaction-only methods, reducing average search time by 54% and 30%, respectively. Full article

Mobile robot olfaction of toxic and hazardous odor sources is of great significance in anti-terrorism, disaster prevention, and control scenarios. Aiming at the problems of low search efficiency and easily falling into a local optimum of the current odor source localization strategies, the paper proposes the adaptive space-aware Infotaxis II algorithm. To improve the tracking efficiency of robots, a new reward function is designed by considering the space information and emphasizing the exploration behavior of robots. Considering the enhancement in exploratory behavior, an adaptive navigation-updated mechanism is proposed to adjust the movement range of robots in real time through information entropy to avoid an excessive exploration behavior during the search process, which may lead the robot to fall into a local optimum. Subsequently, an improved adaptive cosine salp swarm algorithm is applied to confirm the optimal information adaptive parameter. Comparative simulation experiments between ASAInfotaxis II and the classical search strategies are carried out in 2D and 3D scenarios regarding the search efficiency and search behavior, which show that ASAInfotaxis II is competent to improve the search efficiency to a larger extent and achieves a better balance between exploration and exploitation behaviors. Full article

The spatial distribution of gas emitted from an odor source provides valuable information regarding the composition, size, and localization of the odor source. Surface-enhanced Raman scattering (SERS) gas sensors exhibit ultra-high sensitivity, molecular specificity, rapid response, and large-area detection. In this paper, a SERS gas sensor array was developed for visualizing the spatial distribution of gas evaporated from benzaldehyde and 4-ethylbenzaldehyde odor sources. The SERS spectra of the gas were collected by scanning the sensor array using an automatic detection system. The non-negative matrix factorization algorithm was employed to extract feature and concentration information at each spot on the sensor array. A heatmap image was generated for visualizing the gas spatial distribution using concentration information. Gaussian fitting was applied to process the image for localizing the odor source. The size of the odor source was estimated using the processed image. Moreover, the spectra of benzaldehyde, 4-ethylbenzaldehyde, and their gas mixture were simultaneously detected using one SERS sensor array. The feature information was recognized using a convolutional neural network with an accuracy of 98.21%. As a result, the benzaldehyde and 4-ethylbenzaldehyde odor sources were identified and visualized. Our research findings have various potential applications, including odor source localization, environmental monitoring, and healthcare. Full article

Cnaphalocrocis medinalis (Lepidoptera: Crambidae) is a migratory insect pest on rice crops. The migratory C. medinalis population in a particular location may be immigrants, local populations, emigrants, or a mix of these. Immigrants are strongly attracted to plant odor. We conducted research to identify the olfactory receptors in a floral scent mixture that is strongly attractive to C. medinalis. Through gene cloning, 12 olfactory receptor (OR) genes were amplified and expressed in Xenopus oocytes in vitro, and three of them were found to be responsive to plant foliar and floral volatiles. These were CmedOR31, a specific receptor for geraniol; CmedOR32, a broad-spectrum OR gene that responded to both foliar and floral odors; and CmedOR1, which strongly responded to 10⁻⁴ M phenylacetaldehyde. The electrophysiological response to phenylacetaldehyde was extremely high, with a current of 3200 ± 86 nA and an extremely high sensitivity. We compared the phylogenetic tree and sequence similarity of CmedOR genes and found that CmedOR1 belonged to a uniquely conserved OR pedigree in the evolution of Glossata species, and the ORs of this pedigree strongly responded to phenylacetaldehyde. The expression of OR1 was significantly higher in the females than in the males. Localization of CmedOR1 in the antennae of C. medinalis by fluorescence in situ hybridization showed that CmedOR1 was expressed in both males and females. CmedOR1 may be an odor receptor used by females to locate food sources. The function of these ORs and their role in pest monitoring were discussed. Full article

The study examines decentralized waste treatment in an urban setting with a high-density population of 2500 inhab./km². The co-digestion of food and garden waste was assumed by using several mid-size digesters, while centralized biogas and digestate valorization was considered. The studied configuration generates electricity and thermal energy, covering 1.3% of the residential electricity demand and 3.2% of thermal demand. The use of double-turbocharged engines under the most favorable scenario aids cities in reaching sustainability goals. However, the location of treatment plants is a factor that may raise social discomfort and cause a nuisance to citizens. Locating waste plants near residential areas causes discomfort due to possible odors, gaseous emissions, and housing market distortions. Such problematic aspects must be addressed for the decentralized alternative to work. These factors are of great relevance and must be given a practical solution if the circular economic model is to be implemented by considering the insertion of waste streams into the production system and generating local energy sources and raw materials. Full article

Every day, more and more consumers choose to drink bottled water instead of tap water, since they believe that it is superior in quality. One of the criteria used by European consumers to choose bottled water is the geographical region of the spring. The flavor of the water is an additional factor that influences consumers’ choices. As a result, determining the flavor of water is gaining popularity and is thus turning into a prominent field of study. However, studies on the potential environmental factors that affect the sensory characteristics of water (i.e., “terroir” of water) are limited. To this end, we investigated the composition of natural mineral water spring from Mount Smolikas in Greece over a two-year period to find any potential alterations in water composition. The physicochemical parameters (pH, conductivity, turbidity, color, and total hardness) of the water samples were examined, along with their content in metal ions, inorganic salts (cations and anions), and total organic carbon. Additionally, the water samples were analyzed for their content of off-odor volatile compounds (i.e., 2-methylisoborneol and geosmin) that can be naturally found in water. The study also examined the correlation of climate conditions (accumulated rainfall and mean temperature) with the parameters above using a principal component analysis and a multivariate correlation analysis. The results showed that the physicochemical characteristics of water samples complied with European regulations. Metals, anions, and cations were all below the corresponding parametric values established by the European Commission. The off-odor organic compounds, 2-methylisoborneol, and geosmin, had average concentrations of 9.4 and 2.7 ng/L, respectively. Chromium and aluminum elevated concentrations might be attributed to specific ores present near the water source, while pH, conductivity, total hardness, nitrates, and off-odor compounds levels could be fluctuated due to local climate conditions. The study revealed a good positive correlation (>0.7) between the quantity of rainfall and the level of potassium cations. Moreover, a strong negative correlation (>0.9) was observed between magnesium cations and the mean temperature of the local area. The study can be used as a benchmark for future studies to determine the terroir of mineral water. Full article