This paper presents emotion recognition using facial expression. Emotion recognition is widely used in industrial applications where emotion of humans are used to derive conclusions on products and detection of suspective behaviour. In this project we have detected seven emotions of humans which are Happiness, Anger, Sadness, Disgust, Neutral, Surprise and fear. We have taken a set of still images, detected the facial region and the features are extracted. Features are extracted using Bag-Of-Features (BOF) and Histogram of Oriented Gradients (HOG). The feature vectors created by these techniques are used to train Support Vector Machines (SVM) and results are verified against a given test input. We have achieved satisfactory results for emotion recognition. We have found that HOG gives a better result the BOF

http://www.ijariie.com/AdminUploadPdf/Emotion_recognition_using_facial_expressions_ijariie10150.pdf

Emotion recognition using facial expressions

A review of enabling technologies for Internet of Medical Things (IoMT) Ecosystem

This article presents the first-ever hardware-assisted blockchain for simultaneously handling device and data security in smart healthcare. This article presents the hardware security primitive physical unclonable functions (PUF) and blockchain technology together as PUFchain 2.0 with a two-level authentication mechanism. The proposed PUFchain 2.0 security primitive presents a scalable approach by allowing Internet of Medical Things (IoMT) devices to connect and obtain PUF keys from the edge server with an embedded PUF module instead of connecting a PUF module to each device. The PUF key, once assigned to a particular media access control (MAC) address by the miner, will be unique for that MAC address and cannot be assigned to other devices. PUFs are developed based on internal micro-manufacturing process variations during chip fabrication. This property of PUFs is integrated with blockchain by including the PUF key of the IoMT into blockchain for authentication. The robustness of the proposed Proof of PUF-Enabled authentication consensus mechanism in PUFchain 2.0 has been substantiated through test bed evaluation. Arbiter PUFs have been used for the experimental validation of PUFchain 2.0. From the obtained 200 PUF keys, 75% are reliable and the Hamming distance of the PUF module is 48%. Obtained database outputs along with other metrics have been presented for validating the potential of PUFchain 2.0 in smart healthcare. 

/pdf/pufchain-2-0-hardware-assisted-robust-blockchain-for-3q1oho3m.pdf

PUFchain 2.0: Hardware-Assisted Robust Blockchain for Sustainable Simultaneous Device and Data Security in Smart Healthcare

/pdf/pufchain-2-0-hardware-assisted-robust-blockchain-for-11q92i8a.pdf

The rise in the aging population worldwide is already negatively impacting healthcare systems due to the lack of resources. It is envisioned that the development of novel Internet of Things (IoT)-enabled smart city healthcare systems may not only alleviate the stress on the current healthcare systems but may significantly improve the overall quality of life of the elderly. As more elderly homes are fitted with IoT, and intelligent healthcare becomes the norm, there is a need to develop innovative augmented reality (AR) based applications and services that make it easier for caregivers to interact with such systems and assist the elderly on a daily basis. This paper proposes, develops, and validates an AR and IoT-enabled healthcare system to be used by caregivers. The proposed system is based on a smart city IoT middleware platform and provides a standardized, intuitive and non-intrusive way to deliver elderly person's information to caregivers. We present our prototype, and our experimental results show the efficiency of our system in IoT object detection and relevant information retrieval tasks. The average execution time, including object detection, communicating with a server, and rendering the results in the application, takes on average between 767ms and 1,283ms.

Augmented Reality-Assisted Healthcare System for Caregivers in Smart Regions

For any organization to be successful, key factors are the employees and managers working for it. If the manpower is not mentally strong, then progress may not be up to the mark. Having everything smart inside an organization won’t be able to heal the mental health of employees. Healing mental health could only be achieved by smart utilization of smart infrastructure. Every individual is stressed or effected by the current lifestyle, let alone pandemics or other major events. Through everything, for an individual to move forward, a little encouragement with technology shouldn’t be difficult. Being able to analyze the emotions, understand the sudden yet major lluctuations or slow yet harmful changes in the stress levels is very important in order to stay mentally healthy. Keeping everything in consideration, iMirror, a device to maintain the healthy stress response among individuals is proposed in this research. Experimental results show that the proposed iMirror has an accuracy of 97% in automatically determining stress level.

Pritivi Rajkumar

Papers

iMirror: A Smart Mirror for Stress Detection in the IoMT Framework for Advancements in Smart Cities