scholarly journals COGNITIVE INTERNET OF THINGS USING MQTT PROTOCOL FOR SMART DIAGNOSIS SYSTEM

2019 ◽  
Vol 2 (3) ◽  
pp. 30-37
Author(s):  
Eman K. Jassim ◽  
Emad H. AL-Hemiray
Keyword(s):  
Internet Of Things ◽  
Recognition System ◽  
Facial Emotion ◽  
Software Components ◽  
Human Face ◽  
Cognitive Computing ◽  
Live Video ◽  
Surrounding Environment ◽  
Recognition Software ◽  
Cognitive Internet Of Things

Cognitive Internet of Things (CIoT) is the next leap towards enhancing the accuracy and effectiveness of Internet of Things (IoT) technology used in combination with cognitive computing that has a significant role in healthcare and diseases diagnosis. The work in this paper proposes a system to diagnose the sensitivity toward sound and light by developing a mechanism based on facial emotions recognition system that integrate with IoT protocols and cloud computing. The proposed system was achieved by establishing a cognitive IoT environment composed of hardware and software components that practically implemented in a laboratory to identify the behavior of people suffering from sensitivity toward sound and light. This behavior was observed by monitoring human face emotions through a live video capturing using camera and image processing using facial emotion recognition software. Emotions values obtained was examined and collected in a cloud using (MQTT) protocol. These emotions were classified as normal and abnormal. Normal state give the impression that the surrounding environment is appropriate for people senses and they do not suffer from any discomfort, therefore the system works on a mechanism to increase the intensities of sound or light in this environment and vice versa.

scholarly journals Opening Doors Using Internet Of Things (IoT) Based Face Recognition

2021 ◽  
Vol 1 (2) ◽  
Author(s):  
Wahyu Ariansyah ◽  
Dirja Nur Ilham ◽  
Khairuman Khairuman ◽  
Rudi Arif Candra
Keyword(s):  
Image Processing ◽  
Feature Extraction ◽  
Face Recognition ◽  
Internet Of Things ◽  
Digital Image Processing ◽  
Recognition System ◽  
Human Face ◽  
Face Recognition System ◽  
The Face ◽  
Primary Means

Face recognition is a digital image processing approach that uses face photographs as input to identify a person. Face recognition is important since the face is a person's primary means of identification because the shape of a person's face differs significantly, which is easy to do intuitively using the visual senses. Image processing, face detection, feature extraction, and classification are all aspects of the face recognition system, which seeks to determine whether the image obtained is a person's face stored in the database. Principles of operation If a human face appears in front of the camera, the system quickly executes a facial recognition procedure and compares the face to facial data kept on the website. If a face detected by the camera matches the face stored on the website, the solenoid will automatically be in the on position or the door will be open, and vice versa, if the face detected by the camera does not match, the solenoid will remain in the off position or the door will remain locked. This tool can be used to improve the security system on the door of a private room or a room that can only be accessed by certain people.

scholarly journals Real-Time Facial Emotion Recognition Framework for Employees of Organizations Using Raspberry-Pi

2021 ◽  
Vol 11 (22) ◽  
pp. 10540
Author(s):  
Navjot Rathour ◽  
Zeba Khanam ◽  
Anita Gehlot ◽  
Rajesh Singh ◽  
Mamoon Rashid ◽  
...  
Keyword(s):  
Emotion Recognition ◽  
Real Time ◽  
Real Life ◽  
Recognition System ◽  
Facial Emotion Recognition ◽  
Facial Emotion ◽  
Raspberry Pi ◽  
Input Device ◽  
Facial Emotions ◽  
Deep Network

There is a significant interest in facial emotion recognition in the fields of human–computer interaction and social sciences. With the advancements in artificial intelligence (AI), the field of human behavioral prediction and analysis, especially human emotion, has evolved significantly. The most standard methods of emotion recognition are currently being used in models deployed in remote servers. We believe the reduction in the distance between the input device and the server model can lead us to better efficiency and effectiveness in real life applications. For the same purpose, computational methodologies such as edge computing can be beneficial. It can also encourage time-critical applications that can be implemented in sensitive fields. In this study, we propose a Raspberry-Pi based standalone edge device that can detect real-time facial emotions. Although this edge device can be used in variety of applications where human facial emotions play an important role, this article is mainly crafted using a dataset of employees working in organizations. A Raspberry-Pi-based standalone edge device has been implemented using the Mini-Xception Deep Network because of its computational efficiency in a shorter time compared to other networks. This device has achieved 100% accuracy for detecting faces in real time with 68% accuracy, i.e., higher than the accuracy mentioned in the state-of-the-art with the FER 2013 dataset. Future work will implement a deep network on Raspberry-Pi with an Intel Movidious neural compute stick to reduce the processing time and achieve quick real time implementation of the facial emotion recognition system.

scholarly journals An Amateur Drone Surveillance System Based on the Cognitive Internet of Things

2018 ◽  
Vol 56 (1) ◽  
pp. 29-35 ◽  
Author(s):  
Guoru Ding ◽  
Qihui Wu ◽  
Linyuan Zhang ◽  
Yun Lin ◽  
Theodoros A. Tsiftsis ◽  
...  
Keyword(s):  
Internet Of Things ◽  
Surveillance System ◽  
Cognitive Internet Of Things

scholarly journals Introduction to the Special Issue: Applications of Internet of Things

Symmetry ◽  
2018 ◽  
Vol 10 (9) ◽  
pp. 374 ◽  
Author(s):  
Chi-Hua Chen ◽  
Eyhab Al-Masri ◽  
Feng-Jang Hwang ◽  
Despo Ktoridou ◽  
Kuen-Rong Lo
Keyword(s):  
Internet Of Things ◽  
Smart Home ◽  
Data Science ◽  
Cooperative Spectrum Sensing ◽  
Smart Homes ◽  
Recognition System ◽  
Special Issue ◽  
Smart Transportation ◽  
User Classification ◽  
Novel Approach

This editorial introduces the special issue, entitled “Applications of Internet of Things”, of Symmetry. The topics covered in this issue fall under four main parts: (I) communication techniques and applications, (II) data science techniques and applications, (III) smart transportation, and (IV) smart homes. Four papers on sensing techniques and applications are included as follows: (1) “Reliability of improved cooperative communication over wireless sensor networks”, by Chen et al.; (2) “User classification in crowdsourcing-based cooperative spectrum sensing”, by Zhai and Wang; (3) “IoT’s tiny steps towards 5G: Telco’s perspective”, by Cero et al.; and (4) “An Internet of things area coverage analyzer (ITHACA) for complex topographical scenarios”, by Parada et al. One paper on data science techniques and applications is as follows: “Internet of things: a scientometric review”, by Ruiz-Rosero et al. Two papers on smart transportation are as follows: (1) “An Internet of things approach for extracting featured data using an AIS database: an application based on the viewpoint of connected ships”, by He et al.; and (2) “The development of key technologies in applications of vessels connected to the Internet”, by Tian et al. Two papers on smart home are as follows: (1) “A novel approach based on time cluster for activity recognition of daily living in smart homes”, by Liu et al.; and (2) “IoT-based image recognition system for smart home-delivered meal services”, by Tseng et al.

scholarly journals Smart Door / COVID-19 Face Mask Detection

2021 ◽  
Vol 10 (9) ◽  
pp. 87-92
Author(s):  
Pavan Narayana A ◽  
◽  
Janardhan Guptha S ◽  
Deepak S ◽  
Pujith Sai P ◽  
...  
Keyword(s):  
Internet Of Things ◽  
Open Source ◽  
Face Mask ◽  
Young Lady ◽  
Grayscale Image ◽  
Human Face ◽  
Happy Life ◽  
Public Areas ◽  
The Face ◽  
Human Faces

January 27 2020, a day that will be remembered by the Indian people for a few decades, where a deadly virus peeped into a life of a young lady and till now it has been so threatening as it took up the life of 3.26 lakh people just in India. With the start of the virus government has made mandatory to wear masks when we go out in to crowded or public areas such as markets, malls, private gatherings and etc. So, it will be difficult for a person in the entrance to check whether everyone one are entering with a mask, in this paper we have designed a smart door face mask detection to check whether who are wearing or not wearing mask. By using different technologies such as Open CV, MTCNN, CNN, IFTTT, ThingSpeak we have designed this face mask detection. We use python to program the code. MTCNN using Viola- Jones algorithm detects the human faces present in the screen The Viola-Jones algorithm first detects the face on the grayscale image and then finds the location on the colored image. In this algorithm MTCNN first detects the face in grayscale image locates it and then finds this location on colored image. CNN for detecting masks in the human face is constructed using sample datasets and MobileNetV2 which acts as an object detector in our case the object is mask. ThingSpeak is an open-source Internet of things application used to display the information we get form the smart door. This deployed application can also detect when people are moving. So, with this face mask detection, as a part to stop the spread of the virus, we ensure that with this smart door we can prevent the virus from spreading and can regain our happy life.

An Overview of Cognitive Internet of Things

2021 ◽  
pp. 65-82
Author(s):  
Fariha Eusufzai ◽  
Tahmidul Haq ◽  
Sumit Chowdhury ◽  
Shohani Sahren ◽  
Saifur Rahman Sabuj
Keyword(s):  
Internet Of Things ◽  
Cognitive Internet Of Things
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