Tahereh Tamadon | Searcharxiv

arXiv2022

A Survey on Crowdsourcing Applications in Smart Cities

With the emergence of the Internet of things (IoT), human life is now progressing towards smartification faster than ever before. Thus, smart cities become automated in different aspects such as business, education, economy, medicine, and urban areas. Since smartification requires a variety of dynamic information in different urban dimensions, mobile crowdsourcing has gained importance in smart cities. This chapter systematically reviews the related applications of smart cities that use mobile crowdsourcing for data acquisition. For this purpose, the applications are classified as environmental, urban life, and transportation categories and then investigated in detail. This survey helps in understanding the current situation of smart cities from the viewpoint of crowdsourcing and discusses the future research directions in this field.

cs.HC↗

arXiv2022

Application of artificial intelligence techniques for automated detection of myocardial infarction: A review

Myocardial infarction (MI) results in heart muscle injury due to receiving insufficient blood flow. MI is the most common cause of mortality in middle-aged and elderly individuals around the world. To diagnose MI, clinicians need to interpret electrocardiography (ECG) signals, which requires expertise and is subject to observer bias. Artificial intelligence-based methods can be utilized to screen for or diagnose MI automatically using ECG signals. In this work, we conducted a comprehensive assessment of artificial intelligence-based approaches for MI detection based on ECG as well as other biophysical signals, including machine learning (ML) and deep learning (DL) models. The performance of traditional ML methods relies on handcrafted features and manual selection of ECG signals, whereas DL models can automate these tasks. The review observed that deep convolutional neural networks (DCNNs) yielded excellent classification performance for MI diagnosis, which explains why they have become prevalent in recent years. To our knowledge, this is the first comprehensive survey of artificial intelligence techniques employed for MI diagnosis using ECG and other biophysical signals.

eess.SP↗