scholarly journals AMSense: How Mobile Sensing Platforms Capture Pedestrian/Cyclist Spatiotemporal Properties in Cities

2020 ◽  
pp. 0-0 ◽  
Author(s):  
Alphonse Vial ◽  
Winnie Daamen ◽  
Aaron Yi Ding ◽  
Bart van Arem ◽  
Serge Hoogendoorn
Keyword(s):  
Mobile Sensing ◽  
Sensing Platforms

scholarly journals A Review on Scaling Mobile Sensing Platforms for Human Activity Recognition: Challenges and Recommendations for Future Research

IoT ◽  
2020 ◽  
Vol 1 (2) ◽  
pp. 451-473
Author(s):  
Liliana I. Carvalho ◽  
Rute C. Sofia
Keyword(s):  
Activity Recognition ◽  
Human Activity ◽  
Large Scale ◽  
Human Activity Recognition ◽  
Mobile Sensing ◽  
Future Research ◽  
Raising Awareness ◽  
Sensing Platforms ◽  
And Behavior ◽  
Personal Devices

Mobile sensing has been gaining ground due to the increasing capabilities of mobile and personal devices that are carried around by citizens, giving access to a large variety of data and services based on the way humans interact. Mobile sensing brings several advantages in terms of the richness of available data, particularly for human activity recognition. Nevertheless, the infrastructure required to support large-scale mobile sensing requires an interoperable design, which is still hard to achieve today. This review paper contributes to raising awareness of challenges faced today by mobile sensing platforms that perform learning and behavior inference with respect to human routines: how current solutions perform activity recognition, which classification models they consider, and which types of behavior inferences can be seamlessly provided. The paper provides a set of guidelines that contribute to a better functional design of mobile sensing infrastructures, keeping scalability as well as interoperability in mind.

scholarly journals Intermittent Information-Driven Multi-Agent Area-Restricted Search

Entropy ◽  
2020 ◽  
Vol 22 (6) ◽  
pp. 635
Author(s):  
Branko Ristic ◽  
Alex Skvortsov
Keyword(s):  
Search Strategy ◽  
Mobile Sensing ◽  
Probability Of Detection ◽  
False Alarms ◽  
Global Knowledge ◽  
Sensing Platforms ◽  
Multi Agent ◽  
Two Phases ◽  
Dependent Probability ◽  
Displacement Phase

The problem is a two-dimensional area-restricted search for a target using a coordinated team of autonomous mobile sensing platforms (agents). Sensing is characterised by a range-dependent probability of detection, with a non-zero probability of false alarms. The context is underwater surveillance using a swarm of amphibious drones equipped with active sonars. The paper develops an intermittent information-driven search strategy, which alternates between two phases: the fast and non-receptive displacement phase (called the ballistic phase) with a slow displacement and sensing phase (called the diffusive phase). The proposed multi-agent search strategy is carried out in a decentralised manner, which means that all computations (estimation and motion control) are done locally. Coordination of agents is achieved by exchanging the data with the neighbours only, in a manner which does not require global knowledge of the communication network topology.

Model Predictive Control of a Tail-Actuated Robotic Fish

2016 ◽  
Author(s):  
Maria L. Castaño ◽  
Xiaobo Tan
Keyword(s):  
Model Predictive Control ◽  
Predictive Control ◽  
Aquatic Ecosystems ◽  
Path Following ◽  
Mobile Sensing ◽  
Robotic Fish ◽  
Nonlinear Model Predictive Control ◽  
Underwater Robots ◽  
Sensing Platforms ◽  
Tail Beat

The increase of potential threats to the integrity of our aquatic ecosystems has caused global concerns which have led to interest in the use autonomous aquatic robots to monitor such environments. In recent years, underwater robots that propel and maneuver themselves like real fish, often called robotic fish, have emerged as mobile sensing platforms for freshwater and marine environments. These robots achieve locomotion via actively controlled fins, and actuation is often achieved via oscillatory inputs. Given these types of applications, accuracy and energy-saving in trajectory control is of importance for mission successes. In this work, we propose a nonlinear model predictive control (NMPC) approach to path following of a tail-actuated robotic fish. In this design, we use bias and amplitude of the tail-beat as the input to be determined by the NMPC. The effectiveness of the proposed approach is demonstrated via simulation.

Sensors for robotic perception. Part two: positional and environmental awareness

2015 ◽  
Vol 42 (6) ◽  
pp. 502-507 ◽  
Author(s):  
Robert Bogue
Keyword(s):  
Mobile Robots ◽  
Autonomous Underwater Vehicles ◽  
Mobile Sensing ◽  
Automated Guided Vehicles ◽  
Short Introduction ◽  
Content Type ◽  
Hazard Detection ◽  
Sensing Platforms ◽  
Sonar Imaging ◽  
Self Driving Cars

Purpose – The purpose of this article is to illustrate how sensors impart perceptive capabilities to robots. This is the second part of a two-part article. This second part considers positional awareness and sensing in the external environment, notably but not exclusively by autonomous, mobile robots. Design/methodology/approach – Following a short introduction, this article first discusses positional sensing and navigation by mobile robots, including self-driving cars, automated guided vehicles, unmanned aerial vehicles (UAVs) and autonomous underwater vehicles (AUVs). It then considers sensing with UAVs and AUVs, and finally discusses robots for hazard detection. Brief concluding comments are drawn. Findings – This shows that sensors based on a multitude of techniques confer navigational capabilities to mobile robots, including LIDARs, radar, sonar, imaging and inertial sensing devices. UAVs, AUVs and mobile terrestrial robots can be equipped with all manner of sensors to create detailed terrestrial and underwater maps, monitor air and water quality, locate pollution and detect hazards. While existing sensors are used widely, many new devices are now being developed to meet specific requirements and to comply with size, weight and cost restraints. Originality/value – The use of mobile robots is growing rapidly, and this article provides a timely account of how sensors confer them with positional awareness and allow them to act as mobile sensing platforms.

scholarly journals Opportunistic Mobile Sensing in the Fog

2018 ◽  
Vol 2018 ◽  
pp. 1-18 ◽  
Author(s):  
Rolando Menchaca-Mendez ◽  
Brayan Luna-Nuñez ◽  
Ricardo Menchaca-Mendez ◽  
Arturo Yee-Rendon ◽  
Rolando Quintero ◽  
...  
Keyword(s):  
Internet Of Things ◽  
Distributed Algorithms ◽  
Mobile Sensing ◽  
Sensory Data ◽  
Sensing Applications ◽  
Sensing Platforms ◽  
Simulation Based ◽  
Detailed Simulation ◽  
Software Platforms ◽  
Personal Devices

The increasing adoption of mobile personal devices and Internet of Things devices is leveraging the emergence of a wide variety of opportunistic sensing applications. However, the designers of this type of applications face a set of technical challenges related to the limitations and heterogeneity of the hardware and software platforms and to the dynamics of the scenarios where they are deployed. In this paper, we introduce a Semantic-Centric Fog-based framework aimed at effectively and efficiently supporting this type of applications. The proposed framework is composed of local and distributed algorithms that support the establishment and coordination of sensing tasks in the Fog. First, it performs ontology-driven in-network processing to locate the most adequate devices to carry out a given sensing task and then, it establishes efficient multihop routes that are used to coordinate relevant devices and to transport the collected sensory data to Fog sinks. We present a set of theorems that prove that the proposed algorithms are correct and the results of a series of detailed simulation-based experiments in NS3 that characterize the performance of the proposed platform. The results show that the proposed framework outperforms traditional sensing platforms that are based on centralized services.

A label-free fluorescent aptasensor based on HCR and G-quadruplex DNAzymes for the detection of prostate-specific antigen

The Analyst ◽  
2021 ◽  
Author(s):  
Ruirui Zhao ◽  
Lu Zhao ◽  
Haidi Feng ◽  
Xiaoliang Chen ◽  
Huilin Zhang ◽  
...  
Keyword(s):  
Prostate Specific Antigen ◽  
Specific Antigen ◽  
Label Free ◽  
Fluorescence Sensing ◽  
Sensing Platforms ◽  
G Quadruplex ◽  
Fluorescent Aptasensor

Fluorescence sensing platforms based on HCR and G-quadruplex DNAzyme amplification strategies for the detection of prostate-specific antigen.

scholarly journals New Orthophoto Generation Strategies from UAV and Ground Remote Sensing Platforms for High-Throughput Phenotyping

2021 ◽  
Vol 13 (5) ◽  
pp. 860
Author(s):  
Yi-Chun Lin ◽  
Tian Zhou ◽  
Taojun Wang ◽  
Melba Crawford ◽  
Ayman Habib
Keyword(s):  
Remote Sensing ◽  
Control Strategies ◽  
Target Function ◽  
Canopy Cover ◽  
Surface Model ◽  
Flowering Date ◽  
Sensing Platforms ◽  
Geolocation Accuracy ◽  
New Strategies

Remote sensing platforms have become an effective data acquisition tool for digital agriculture. Imaging sensors onboard unmanned aerial vehicles (UAVs) and tractors are providing unprecedented high-geometric-resolution data for several crop phenotyping activities (e.g., canopy cover estimation, plant localization, and flowering date identification). Among potential products, orthophotos play an important role in agricultural management. Traditional orthophoto generation strategies suffer from several artifacts (e.g., double mapping, excessive pixilation, and seamline distortions). The above problems are more pronounced when dealing with mid- to late-season imagery, which is often used for establishing flowering date (e.g., tassel and panicle detection for maize and sorghum crops, respectively). In response to these challenges, this paper introduces new strategies for generating orthophotos that are conducive to the straightforward detection of tassels and panicles. The orthophoto generation strategies are valid for both frame and push-broom imaging systems. The target function of these strategies is striking a balance between the improved visual appearance of tassels/panicles and their geolocation accuracy. The new strategies are based on generating a smooth digital surface model (DSM) that maintains the geolocation quality along the plant rows while reducing double mapping and pixilation artifacts. Moreover, seamline control strategies are applied to avoid having seamline distortions at locations where the tassels and panicles are expected. The quality of generated orthophotos is evaluated through visual inspection as well as quantitative assessment of the degree of similarity between the generated orthophotos and original images. Several experimental results from both UAV and ground platforms show that the proposed strategies do improve the visual quality of derived orthophotos while maintaining the geolocation accuracy at tassel/panicle locations.

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