scholarly journals Scalable Gas Sensing, Mapping, and Path Planning via Decentralized Hilbert Maps

Sensors ◽  
2019 ◽  
Vol 19 (7) ◽  
pp. 1524 ◽  
Author(s):  
Pingping Zhu ◽  
Silvia Ferrari ◽  
Julian Morelli ◽  
Richard Linares ◽  
Bryce Doerr
Keyword(s):  
Path Planning ◽  
Large Scale ◽  
Gas Sensing ◽  
Data Communication ◽  
Communication Strategy ◽  
Outdoor Environments ◽  
Planning Methods ◽  
Multi Class Classification ◽  
Indoor And Outdoor Environments ◽  
Gas Distribution Mapping

This paper develops a decentralized approach to gas distribution mapping (GDM) and information-driven path planning for large-scale distributed sensing systems. Gas mapping is performed using a probabilistic representation known as a Hilbert map, which formulates the mapping problem as a multi-class classification task and uses kernel logistic regression to train a discriminative classifier online. A novel Hilbert map information fusion method is presented for rapidly merging the information from individual robot maps using limited data communication. A communication strategy that implements data fusion among many robots is also presented for the decentralized computation of GDMs. New entropy-based information-driven path-planning methods are developed and compared to existing approaches, such as particle swarm optimization (PSO) and random walks (RW). Numerical experiments conducted in simulated indoor and outdoor environments show that the information-driven approaches proposed in this paper far outperform other approaches, and avoid mutual collisions in real time.

A Novel Static Path Planning Method for Mobile Anchor-Assisted Localization in Wireless Sensor Networks

2020 ◽  
Vol 10 ◽  
Author(s):  
Abdelhady M. Naguib ◽  
Shahzad Ali
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Path Planning ◽  
Sensor Node ◽  
Large Scale ◽  
Performance Metrics ◽  
Wireless Sensor ◽  
Anchor Node ◽  
Mobile Anchor ◽  
Planning Methods

Background: Many applications of Wireless Sensor Networks (WSNs) require awareness of sensor node’s location but not every sensor node can be equipped with a GPS receiver for localization, due to cost and energy constraints especially for large-scale networks. For localization, many algorithms have been proposed to enable a sensor node to be able to determine its location by utilizing a small number of special nodes called anchors that are equipped with GPS receivers. In recent years a promising method that significantly reduces the cost is to replace the set of statically deployed GPS anchors with one mobile anchor node equipped with a GPS unit that moves to cover the entire network. Objectives: This paper proposes a novel static path planning mechanism that enables a single anchor node to follow a predefined static path while periodically broadcasting its current location coordinates to the nearby sensors. This new path type is called SQUARE_SPIRAL and it is specifically designed to reduce the collinearity during localization. Results: Simulation results show that the performance of SQUARE_SPIRAL mechanism is better than other static path planning methods with respect to multiple performance metrics. Conclusion: This work includes an extensive comparative study of the existing static path planning methods then presents a comparison of the proposed mechanism with existing solutions by doing extensive simulations in NS-2.

An Improved Control for Large-Scale Wireless Sensor Networks

2011 ◽  
Vol 474-476 ◽  
pp. 2315-2319
Author(s):  
Shuang Xia Han ◽  
Lu Zhang ◽  
Jian Wen Fang
Keyword(s):  
Wireless Sensor Networks ◽  
Energy Consumption ◽  
Control Strategy ◽  
Topology Control ◽  
Control Algorithm ◽  
Large Scale ◽  
Data Communication ◽  
Communication Strategy ◽  
Wireless Sensor ◽  
Reliability Control

A 3-layer topology is proposed to solve the problem of the incompatibility of the traditional topology structure in large-scale WSN. The data communication strategy for each level have been analysed, and an topology control algorithm for top-level is brought up based on the bottleneck-nodes, which will provide higher reliability control for the key-level. The experimental results indicated that, the new topology control strategy will contribute to balance the communication load of the nodes, and the energy consumption in the key-level reduce remarkably.

scholarly journals Gas distribution mapping of multiple odour sources using a mobile robot

Robotica ◽  
2009 ◽  
Vol 27 (2) ◽  
pp. 311-319 ◽  
Author(s):  
Amy Loutfi ◽  
Silvia Coradeschi ◽  
Achim J. Lilienthal ◽  
Javier Gonzalez
Keyword(s):  
Mobile Robot ◽  
Spatial Information ◽  
Gas Distribution ◽  
Outdoor Environments ◽  
Distribution Mapping ◽  
Multi Level ◽  
Indoor And Outdoor Environments ◽  
Gas Distribution Mapping ◽  
Indoor And Outdoor

SUMMARYMobile olfactory robots can be used in a number of relevant application areas where a better understanding of a gas distribution is needed, such as environmental monitoring and safety and security related fields. In this paper, we present a method to integrate the classification of odours together with gas distribution mapping. The resulting odour map is then correlated with the spatial information collected from a laser range scanner to form a combined map. Experiments are performed using a mobile robot in large and unmodified indoor and outdoor environments. Multiple odour sources are used and are identified using only transient information from the gas sensor response. The resulting multi-level map can be used as a representation of the collected odour data.

scholarly journals Visualizing Large-Scale Building Information Modeling Models within Indoor and Outdoor Environments Using a Semantics-Based Method

2021 ◽  
Vol 10 (11) ◽  
pp. 756
Author(s):  
Qingxiang Chen ◽  
Jing Chen ◽  
Wumeng Huang
Keyword(s):  
Large Scale ◽  
Building Information Modeling ◽  
Information Modeling ◽  
Outdoor Environment ◽  
City Development ◽  
Outdoor Environments ◽  
Building Information ◽  
Virtual Globes ◽  
Indoor And Outdoor Environments ◽  
Indoor And Outdoor

Building information modeling (BIM), with detailed geometry and semantics of the indoor environment, has become an essential part of smart city development and city information modeling (CIM). However, visualizing large-scale BIM models within geographic information systems (GIS), such as virtual globes, remains a technological challenge with limited hardware resources. Previous methods generally removed indoor features in a single-source (BIM) scene to reduce the computational burden from outdoor views, which have not been applied to the multi-source and -scale geographic environment (e.g., virtual globes). This approach neglected special BIM semantics (e.g., transparent windows), which may miss a part of geographic features or buildings and cause unreasonable visualization. Besides, the method overlooked indoor visualization optimization, which may burden computing resources when visualizing big and complex buildings from indoor views. To address these problems, we propose a semantics-based method for visualizing large-scale BIM models within indoor and outdoor environments. First, we organize large-scale BIM models based on a latitude-longitude grid (LLG) in the outdoor environment; a multilayer cell-and-portal graph is used to index the structure of the BIM model and building entities. Second, we propose a scheduling algorithm to achieve the integrated visualization in indoor and outdoor environments considering BIM semantics. The application of the proposed method to a multi-scale and -source environment confirmed that it can achieve an effective and efficient visualization for huge BIM models in indoor-outdoor scenes. Compared with the previous study, the proposed method considers the BIM semantics and thus can visualize more complete features from outdoor and indoor views of BIM models in the virtual globe. Besides, the study only loads as visible data as possible, which can retain lower the volume of increased geometry, and thus keep a higher frame rate for the tested areas.

Robot mapping in large-scale mixed indoor and outdoor environments

2013 ◽  
Author(s):  
John G. Rogers ◽  
Stuart Young ◽  
Jason Gregory ◽  
Carlos Nieto-Granda ◽  
Henrik I. Christensen
Keyword(s):  
Large Scale ◽  
Outdoor Environments ◽  
Indoor And Outdoor Environments ◽  
Indoor And Outdoor

scholarly journals Revealing the Challenges of Smart Rainwater Harvesting for Integrated and Digital Resilience of Urban Water Infrastructure

Water ◽  
2021 ◽  
Vol 13 (14) ◽  
pp. 1902
Author(s):  
Martin Oberascher ◽  
Aun Dastgir ◽  
Jiada Li ◽  
Sina Hesarkazzazi ◽  
Mohsen Hajibabaei ◽  
...  
Keyword(s):  
Large Scale ◽  
Rainwater Harvesting ◽  
Data Communication ◽  
Integrated System ◽  
Coupled Systems ◽  
Urban Resilience ◽  
System Failures ◽  
Household Level ◽  
Performance Improvements ◽  
Smart Water

Smart rainwater harvesting (RWH) systems can automatically release stormwater prior to rainfall events to increase detention capacity on a household level. However, impacts and benefits of a widespread implementation of these systems are often unknown. This works aims to investigate the effect of a large-scale implementation of smart RWH systems on urban resilience by hypothetically retrofitting an Alpine municipality with smart rain barrels. Smart RWH systems represent dynamic systems, and therefore, the interaction between the coupled systems RWH units, an urban drainage network (UDN) and digital infrastructure is critical for evaluating resilience against system failures. In particular, digital parameters (e.g., accuracy of weather forecasts, or reliability of data communication) can differ from an ideal performance. Therefore, different digital parameters are varied to determine the range of uncertainties associated with smart RWH systems. As the results demonstrate, smart RWH systems can further increase integrated system resilience but require a coordinated integration into the overall system. Additionally, sufficient consideration of digital uncertainties is of great importance for smart water systems, as uncertainties can reduce/eliminate gained performance improvements. Moreover, a long-term simulation should be applied to investigate resilience with digital applications to reduce dependence on boundary conditions and rainfall patterns.

Impacts of Different Winter Storage Conditions on the Physiology of Diutinus Honey Bees (Hymenoptera: Apidae)

2021 ◽  
Author(s):  
Brandon K Hopkins ◽  
Priyadarshini Chakrabarti ◽  
Hannah M Lucas ◽  
Ramesh R Sagili ◽  
Walter S Sheppard
Keyword(s):  
Honey Bees ◽  
The United States ◽  
Storage Conditions ◽  
Colony Losses ◽  
Bee Colony ◽  
Causative Factors ◽  
Outdoor Environments ◽  
Indoor And Outdoor Environments ◽  
Physiological Markers ◽  
Honey Bee Colony Losses

Abstract Global decline in insect pollinators, especially bees, have resulted in extensive research into understanding the various causative factors and formulating mitigative strategies. For commercial beekeepers in the United States, overwintering honey bee colony losses are significant, requiring tactics to overwinter bees in conditions designed to minimize such losses. This is especially important as overwintered honey bees are responsible for colony expansion each spring, and overwintered bees must survive in sufficient numbers to nurse the spring brood and forage until the new ‘replacement’ workers become fully functional. In this study, we examined the physiology of overwintered (diutinus) bees following various overwintering storage conditions. Important physiological markers, i.e., head proteins and abdominal lipid contents were higher in honey bees that overwintered in controlled indoor storage facilities, compared with bees held outdoors through the winter months. Our findings provide new insights into the physiology of honey bees overwintered in indoor and outdoor environments and have implications for improved beekeeping management.

scholarly journals A Hybrid Framework for Mitigating Heading Drift for a Wearable Pedestrian Navigation System through Adaptive Fusion of Inertial and Magnetic Measurements

2021 ◽  
Vol 11 (4) ◽  
pp. 1902
Author(s):  
Liqiang Zhang ◽  
Yu Liu ◽  
Jinglin Sun
Keyword(s):  
Magnetic Measurements ◽  
Inertial Sensor ◽  
Angular Rate ◽  
Human Motion ◽  
Navigation Systems ◽  
Pedestrian Navigation ◽  
Hybrid Framework ◽  
Outdoor Environments ◽  
Adaptive Fusion ◽  
Indoor And Outdoor Environments

Pedestrian navigation systems could serve as a good supplement for other navigation methods or for extending navigation into areas where other navigation systems are invalid. Due to the accumulation of inertial sensing errors, foot-mounted inertial-sensor-based pedestrian navigation systems (PNSs) suffer from drift, especially heading drift. To mitigate heading drift, considering the complexity of human motion and the environment, we introduce a novel hybrid framework that integrates a foot-state classifier that triggers the zero-velocity update (ZUPT) algorithm, zero-angular-rate update (ZARU) algorithm, and a state lock, a magnetic disturbance detector, a human-motion-classifier-aided adaptive fusion module (AFM) that outputs an adaptive heading error measurement by fusing heuristic and magnetic algorithms rather than simply switching them, and an error-state Kalman filter (ESKF) that estimates the optimal systematic error. The validation datasets include a Vicon loop dataset that spans 324.3 m in a single room for approximately 300 s and challenging walking datasets that cover large indoor and outdoor environments with a total distance of 12.98 km. A total of five different frameworks with different heading drift correction methods, including the proposed framework, were validated on these datasets, which demonstrated that our proposed ZUPT–ZARU–AFM–ESKF-aided PNS outperforms other frameworks and clearly mitigates heading drift.

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