scholarly journals Thermal Infrared Sensing for Near Real-Time Data-Driven Fire Detection and Monitoring Systems

Sensors ◽  
2020 ◽  
Vol 20 (23) ◽  
pp. 6803
Author(s):  
Maria João Sousa ◽  
Alexandra Moutinho ◽  
Miguel Almeida
Keyword(s):  
Image Processing ◽  
Situation Awareness ◽  
Thermal Imaging ◽  
Mobile Robotics ◽  
Fire Detection ◽  
Data Driven ◽  
Time Data ◽  
Depth Analysis ◽  
Robotic Perception ◽  
Thermal Cameras

With the increasing interest in leveraging mobile robotics for fire detection and monitoring arises the need to design recognition technology systems for these extreme environments. This work focuses on evaluating the sensing capabilities and image processing pipeline of thermal imaging sensors for fire detection applications, paving the way for the development of autonomous systems for early warning and monitoring of fire events. The contributions of this work are threefold. First, we overview image processing algorithms used in thermal imaging regarding data compression and image enhancement. Second, we present a method for data-driven thermal imaging analysis designed for fire situation awareness in robotic perception. A study is undertaken to test the behavior of the thermal cameras in controlled fire scenarios, followed by an in-depth analysis of the experimental data, which reveals the inner workings of these sensors. Third, we discuss key takeaways for the integration of thermal cameras in robotic perception pipelines for autonomous unmanned aerial vehicle (UAV)-based fire surveillance.

scholarly journals Towards Providing Effective Data-Driven Responses to Predict the Covid-19 in São Paulo and Brazil

Sensors ◽  
2021 ◽  
Vol 21 (2) ◽  
pp. 540
Author(s):  
Fabio Amaral ◽  
Wallace Casaca ◽  
Cassio M. Oishi ◽  
José A. Cuminato
Keyword(s):  
Learning Strategies ◽  
Time Series Data ◽  
Sao Paulo ◽  
The State ◽  
Data Driven ◽  
Series Data ◽  
São Paulo ◽  
Time Data ◽  
Unified Framework ◽  
Infected People

São Paulo is the most populous state in Brazil, home to around 22% of the country’s population. The total number of Covid-19-infected people in São Paulo has reached more than 1 million, while its total death toll stands at 25% of all the country’s fatalities. Joining the Brazilian academia efforts in the fight against Covid-19, in this paper we describe a unified framework for monitoring and forecasting the Covid-19 progress in the state of São Paulo. More specifically, a freely available, online platform to collect and exploit Covid-19 time-series data is presented, supporting decision-makers while still allowing the general public to interact with data from different regions of the state. Moreover, a novel forecasting data-driven method has also been proposed, by combining the so-called Susceptible-Infectious-Recovered-Deceased model with machine learning strategies to better fit the mathematical model’s coefficients for predicting Infections, Recoveries, Deaths, and Viral Reproduction Numbers. We show that the obtained predictor is capable of dealing with badly conditioned data samples while still delivering accurate 10-day predictions. Our integrated computational system can be used for guiding government actions mainly in two basic aspects: real-time data assessment and dynamic predictions of Covid-19 curves for different regions of the state. We extend our analysis and investigation to inspect the virus spreading in Brazil in its regions. Finally, experiments involving the Covid-19 advance in other countries are also given.

A Novel Embedded System Architecture for Fire Detection Based on Image Processing

2014 ◽  
Vol 608-609 ◽  
pp. 454-458
Author(s):  
Wei Bai ◽  
Chen Yuan Hu
Keyword(s):  
Image Processing ◽  
Embedded System ◽  
System Architecture ◽  
Cooperative Control ◽  
Processing System ◽  
Fire Detection ◽  
System Level ◽  
High Definition ◽  
The Embedded System ◽  
Pass Through

This paper presents novel logic/software co-work architecture for embedded high definition image processing platform, which is built by the considerations of system level, board hardware level, and the tasks partition between CPU processing and programmable logic based on the latest launched System on Chip Field Programmable Gate Array (Soc FPGA) – Xilinx ZC7020. For this case, we comprehensive analyze of the critical data paths: the uniform Advanced Extensible Interface (AXI) processing between processing system (PS) and processing logic (PL), including high definition video pass through PL to PS and PS software processing send to PL for speed up. We have included the transplant of opensource Linux, multiprocessing cooperative control and boot loader in PS side. Since the general platform is proposed, a fire detection approach based on high definition image processing is implemented. Experiment results indicated the feasibility and universality of the embedded system architecture.

scholarly journals Automated processing of thermal imaging to detect COVID-19

2020 ◽  
Author(s):  
Rafael Y. Brzezinski ◽  
Neta Rabin ◽  
Nir Lewis ◽  
Racheli Peled ◽  
Ariel Kerpel ◽  
...  
Keyword(s):  
Image Processing ◽  
Low Income ◽  
Thermal Imaging ◽  
Point Of Care ◽  
Area Under The Curve ◽  
Screening Tools ◽  
Imaging Device ◽  
Thermal Images ◽  
Image Processing Algorithms ◽  
Processing Algorithms

ABSTRACTRapid and sensitive screening tools for SARS-CoV-2 infection are essential to limit the spread of COVID-19 and to properly allocate national resources. Here, we developed a new point-of-care, non-contact thermal imaging tool to detect COVID-19, based on image-processing algorithms and machine learning analysis. We captured thermal images of the back of individuals with and without COVID-19 using a portable thermal camera that connects directly to smartphones. Our novel image processing algorithms automatically extracted multiple texture and shape features of the thermal images and achieved an area under the curve (AUC) of 0.85 in detecting COVID-19 with up to 92% sensitivity. Thermal imaging scores were inversely correlated with clinical variables associated with COVID-19 disease progression. We show, for the first time, that a hand-held thermal imaging device can be used to detect COVID-19. Non-invasive thermal imaging could be used to screen for COVID-19 in out-of-hospital settings, especially in low-income regions with limited imaging resources.

Heart Watch: Dynamical Systems Based Real Time Data Driven ECG Synthesis

2021 ◽  
Author(s):  
Ashutosh Simha ◽  
Suryansh Sharma ◽  
Sujay Narayana ◽  
R. Venkatesh Prasad
Keyword(s):  
Dynamical Systems ◽  
Real Time ◽  
Data Driven ◽  
Time Data ◽  
Real Time Data

A REAL-TIME DATA-DRIVEN CONTROL SYSTEM FOR MULTI-MOTOR-DRIVEN MECHANISMS

2017 ◽  
Vol 32 (6) ◽  
Author(s):  
Huashan Liu ◽  
Lingbin Zeng ◽  
Wuneng Zhou ◽  
Shiqiang Zhu
Keyword(s):  
Control System ◽  
Real Time ◽  
Data Driven ◽  
Time Data ◽  
Real Time Data

Surgeon Assistive Augmented Reality Model with the use of Endoscopic Camera for Line of Vision Calculation

2013 ◽  
pp. 658-674
Author(s):  
Anastasia Daskalaki ◽  
Kostas Giokas ◽  
Dimitris Koutsouris
Keyword(s):  
Image Processing ◽  
Augmented Reality ◽  
Situation Awareness ◽  
User Interfaces ◽  
Medical Data ◽  
Graphical User Interfaces ◽  
Ar Model ◽  
Image Processing Techniques ◽  
Processing Techniques ◽  
Robotic Surgeries

In this paper, the authors describe a surgeon assistive Augmented Reality (AR) model for endoscopic procedures. They analyze the main parts of the model and the processes that need to be established such as, the registration of the patient, the segmentation of medical data, their 3D reconstruction, and the detection of endoscopic instruments and the camera. The authors present two graphical user interfaces, build to serve the needs of segmentation, navigation, and visualization of the final intra-operative scene. By using preoperative data of the patient (MRI-CT) and image processing techniques, the authors can provide a unique view of the surgical scene. The potentials and the advantages of endoscopic-robotic surgeries nowadays can be improved. Augmented surgery scenes with information about the patients underline structures, enables wider situation awareness, precision, and confidence.

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