An efficient real-time architecture for collecting IoT data

IoT applications has some characteristics that set it apart from other fields mainly due to the multitude of different types of sensors producing data. In monitoring applications, data processing requires real-time or soft real-time responses in order to aid systems to make important decisions but also predictive analysis to leverage the potential of IoT by data mining vast datasets. This paper presents an architecture developed to efficiently process and store data coming from an huge number of distributed IoT sensors. The back-end of SeeYourBox services is currently based on the proposed architecture that has proven to be stable and meet all the requirements

Real Time Risk Monitoring in Fine-art with IoT Technology.

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RAMi: a new Real-time internet of medical things Architecture for elderly patient Monitoring

peer reviewedThe aging of the world's population, the willingness of elderly to remain independent, and the recent COVID-19 pandemic have demonstrated the urgent need for home-based diagnostic and patient monitoring systems to reduce the financial and organizational burdens that impact healthcare organizations and professionals. The Internet of Medical Things (IoMT) i.e., all medical devices and applications that connect to health information systems through online computer networks. The IoMT} is one of domains of IoT where the real-time processing of data and reliability are crucial. In this paper, we propose RAMi, which is a Real-Time Architecture for the Monitoring of elderly patients thanks to the Internet of Medical Things. This new architecture associating a Things layer where data is retrieved from sensors or smartphone, a Fog layer built on a smart gateway, Mobile Edge Computing (MEC), a cloud component, blockchain, and Artificial Intelligence (AI) to addresses concerns of IoMT. Data is processed at Fog level, MEC or cloud in function of the workload, resource requirements, and the level of confidentiality. A local blockchain allows workload orchestration between Fog, MEC, and Cloud while a global blockchain secures exchanges and data sharing using smart contracts. Our architecture allows us to follow elderly people and patient during and after their hospitalization. In addition, our architecture allows the use of federated learning to train AI algorithms while respecting privacy and data confidentiality. AI is also used to detect patterns of intrusion.9. Industry, innovation and infrastructur