scholarly journals Activity Recognition in Residential Spaces with Internet of Things Devices and Thermal Imaging

Sensors ◽  
2021 ◽  
Vol 21 (3) ◽  
pp. 988
Author(s):  
Kshirasagar Naik ◽  
Tejas Pandit ◽  
Nitin Naik ◽  
Parth Shah
Keyword(s):  
Internet Of Things ◽  
Activity Recognition ◽  
Thermal Model ◽  
Thermal Image ◽  
Heat Radiation ◽  
Household Activity ◽  
Thermal Images ◽  
Gas Leakage ◽  
3D Space ◽  
Image Pairs

In this paper, we design algorithms for indoor activity recognition and 3D thermal model generation using thermal images, RGB images, captured from external sensors, and the internet of things setup. Indoor activity recognition deals with two sub-problems: Human activity and household activity recognition. Household activity recognition includes the recognition of electrical appliances and their heat radiation with the help of thermal images. A FLIR ONE PRO camera is used to capture RGB-thermal image pairs for a scene. Duration and pattern of activities are also determined using an iterative algorithm, to explore kitchen safety situations. For more accurate monitoring of hazardous events such as stove gas leakage, a 3D reconstruction approach is proposed to determine the temperature of all points in the 3D space of a scene. The 3D thermal model is obtained using the stereo RGB and thermal images for a particular scene. Accurate results are observed for activity detection, and a significant improvement in the temperature estimation is recorded in the 3D thermal model compared to the 2D thermal image. Results from this research can find applications in home automation, heat automation in smart homes, and energy management in residential spaces.

scholarly journals New Gas Leakage Detection System using Internet of Things

2020 ◽  
Vol 7 (7) ◽  
pp. 69-76
Author(s):  
Meteb Altaf ◽  
Alaa Menshawi ◽  
Ruba Al-Skate ◽  
Taghreed Al-Musharraf ◽  
Wejdan Al-Sakaker
Keyword(s):  
Internet Of Things ◽  
Detection System ◽  
Leakage Detection ◽  
Gas Leakage

scholarly journals Design of Optimal Deep Learning based Human Activity Recognition on Sensor Enabled Internet of Things Environment

IEEE Access ◽  
2021 ◽  
pp. 1-1
Author(s):  
Fahd N. Al-Wesabi ◽  
Amani Abdulrahman Albraikan ◽  
Anwer Mustafa Hilal ◽  
Asma Abdulghani Al-Shargabi ◽  
Saleh Alhazbi ◽  
...  
Keyword(s):  
Deep Learning ◽  
Internet Of Things ◽  
Activity Recognition ◽  
Human Activity ◽  
Human Activity Recognition ◽  
Internet Of Things Environment

scholarly journals LPG Gas Detecting Robot Based on IOT

2020 ◽  
Vol 173 ◽  
pp. 01006
Author(s):  
Tanzila Younas ◽  
Deepak Kumar Mukhi ◽  
Mufaddal Saifuddin ◽  
S M Faiz Hassan Zaidi ◽  
M Mahad Fayyaz ◽  
...  
Keyword(s):  
Cost Effectiveness ◽  
Internet Of Things ◽  
Mobile Device ◽  
Warning System ◽  
Potential Hazard ◽  
Leakage Detection ◽  
Liquefied Petroleum Gas ◽  
Human Interference ◽  
Gas Leakage

With new innovations and technologies world besides being facilitated is also subjected to face the threat of major misadventures and disasters. Likewise, Liquefied Petroleum Gas (LPG) is generally used in household for kitchen in general and gas geysers or heaters in winter. Similarly, industries use it for different causes for instance furnace, boiling and get higher production at cheaper rate. Besides, this gas is igneous gas and can cause potential hazard at any time. Hence, in this paper research is made on Internet of Things (IOT) to reduce the chances of such mishaps by presenting a model of microcontroller-based LPG gas detecting and warning system. Furthermore, it explicates the development of self-directed android based mobile device for gas leakage detection that can be installed in all sort of places. Moreover, this device would be containing MQ6 sensor to detect the unwanted outflow and GPS module to locate particular location of leakage what is more Arduino is installed to disseminate information of leakage to different servers like Smartphones, Email and buzzer and shall give display on LCD. Subsequently, it will send the mobile alert to authorized and concerned authorities to take action with in time and there would be buzzer installed. In addition, this device promises automatic working with no need of human interference and assures reliability, efficiency along with cost-effectiveness check-ups of pipeline.

A MODEL BASED ON IOT FOR IMPROVING PROGRAMMING LANGUAGE SKILLS AMONG STUDENTS

2017 ◽  
Vol 5 (2) ◽  
pp. 38
Author(s):  
Kiran Shinde ◽  
Rupali Bhangale
Keyword(s):  
Internet Of Things ◽  
Programming Language ◽  
Activity Recognition ◽  
Human Activity ◽  
Real World ◽  
Language Skills ◽  
Technological Advancement ◽  
Human Intervention ◽  
Proposed Model ◽  
Smart Education

Internet of things (IoT) is the next Buzz word in Computing. It is going to touch much more facets of our lives.It involves real world, physical objects with embedded computational and networking capabilities communicating with one another without human intervention on the global Internet. IoT can be assumed as an umbrella term for interconnected technologies, objects, machines and their services.Due to which objects are communicating   Greater connectivity and technological advancement [1,2] the education has been enriched and expanded. This paper proposes a model for transforming today’s education into SMART education with the use of IOT. There are many areas where human activity recognition is done by using different sensors. Now education sector needs to be connected with such emerging technology.The proposed model will help the students to enhance their grasping level while learning without hesitation.

First Order Statistical Features Thermal Images for Surge Arrester Fault Classification

2016 ◽  
Vol 818 ◽  
pp. 91-95
Author(s):  
Novizon ◽  
Zulkurnain Abdul-Malek
Keyword(s):  
Neural Network ◽  
Extraction Method ◽  
Thermal Image ◽  
Image Features ◽  
Fault Classification ◽  
Contact Method ◽  
Health States ◽  
Thermal Images ◽  
First Order ◽  
Condition Diagnosis

— Thermal imaging technique is a very convenient, versatile and non-contact method which has been used for fault condition diagnosis of electrical equipment. The fault condition diagnosis is composed with data acquisition, data pre-processing, data analysis and decision making. Some important features contain in thermal image can be extracted for equipment condition monitoring and fault diagnosis. This paper attempts to extract some important features from the zinc oxide (ZnO) surge arrester using first order statistical histogram extraction to classify the fault condition using neural network. The experimental work was carried out to capture thermal image of 120 kV rated ZnO surge arrester. The thermal images were segmented and plotted histogram using dedicated software. Some features such as the maximum, minimum, mean, standard deviation, and variance were extracted using the extraction method, classification of aging was carried out using the neural network based on the leakage current values. The health states consist of normal, defection and faulty. The results show that the thermal image features extracted using the extraction method can be used to classify the fault condition of the ZnO surge arresters

scholarly journals Performance Analysis of Three-Dimensional Clustered Device-to-Device Networks for Internet of Things

2017 ◽  
Vol 2017 ◽  
pp. 1-10 ◽  
Author(s):  
Haejoon Jung ◽  
In-Ho Lee
Keyword(s):  
Internet Of Things ◽  
Three Dimensional ◽  
Urban Environments ◽  
Cochannel Interference ◽  
Centralized Control ◽  
D2d Communications ◽  
3D Space ◽  
Device To Device ◽  
The Internet Of Things ◽  
Local File

Internet of things (IoT) is a smart technology that connects anything anywhere at any time. Intelligent device-to-device (D2D) communication, in which devices will communicate with each other autonomously without any centralized control, is an integral part of the Internet of Things (IoT) ecosystem. Thus, for D2D applications such as local file sharing or swarm sensing, we study communications between devices in proximity in ultra-dense urban environments, where devices are stacked vertically and dispersed in the horizontal plane. To reflect the spatiotemporal correlation inherently embedded in the D2D communications, we model and analyze clustered D2D networks in three-dimensional (3D) space based on Thomas cluster process (TCP), where the locations of clusters follow Poisson point process, and cluster members (devices) are normally distributed around their cluster centers. We assume that multiple device pairs in the network can share the same frequency band simultaneously. Thus, in the presence of cochannel interference from both the same cluster and the other clusters, we investigate the coverage probability and the area spectral efficiency of the clustered D2D networks in 3D space.

scholarly journals Human Activity Recognition with Deep Learning: Overview, Challenges & Possibilities

2021 ◽  
Author(s):  
Pranjal Kumar
Keyword(s):  
Deep Learning ◽  
Internet Of Things ◽  
Activity Recognition ◽  
Human Activity ◽  
Recognition System ◽  
The Internet ◽  
Learning Approaches ◽  
The Public ◽  
Sensory Data ◽  
The Internet Of Things

The growing use of sensor tools and the Internet of Things requires sensors to understand the applications. There are major difficulties in realistic situations, though, that can impact the efficiency of the recognition system. Recently, as the utility of deep learning in many fields has been shown, various deep approaches were researched to tackle the challenges of detection and recognition. We present in this review a sample of specialized deep learning approaches for the identification of sensor-based human behaviour. Next, we present the multi-modal sensory data and include information for the public databases which can be used in different challenge tasks for study. A new taxonomy is then suggested, to organize deep approaches according to challenges. Deep problems and approaches connected to problems are summarized and evaluated to provide an analysis of the ongoing advancement in science. By the conclusion of this research, we are answering unanswered issues and providing perspectives into the future.

Sign in / Sign up

Export Citation Format

Share Document