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The Illinois Structural Health Monitoring Project's underlying goal is to minimize the cost of infrastructure inspections though using inexpensive and reliable wireless sensor arrays, significantly reducing the need for physical human inspection. Its main focus has been to monitor bridges using sensor networks. While other wired bridge ...
The value of structural health information is the expected utility gain of a built environment system by information provided by structural health monitoring (SHM).The quantification of the value of structural health information is based on decision analysis adapted to built environment engineering.
Structural health monitoring (SHM) involves the observation and analysis of a system over time using periodically sampled response measurements to monitor changes to the material and geometric properties of engineering structures such as bridges and buildings. In an operational environment, structures degrade with age and use.
Devices embedded in the environment track the physical state of a person for continuous health diagnosis, using as input the data from a network of depth cameras, a sensing floor, or other similar devices. Body-area networks can collect information about an individual's health, fitness, and energy expenditure.
IoT devices can be used to enable remote health monitoring and emergency notification systems. These health monitoring devices can range from blood pressure and heart rate monitors to advanced devices capable of monitoring specialized implants, such as pacemakers, Fitbit electronic wristbands, or advanced hearing aids. [62]
Artificial intelligence utilises massive amounts of data to help with predicting illness, prevention, and diagnosis, as well as patient monitoring. In obstetrics, artificial intelligence is utilized in magnetic resonance imaging, ultrasound, and foetal cardiotocography. AI contributes in the resolution of a variety of obstetrical diagnostic issues.
It is also possible to combine artificial intelligence with edge computing in order to provide industrial edge intelligence solutions. [11] There are many use-cases using AI with IIoT, to name a few: condition monitoring and predictive maintenance, [12] process optimization, [13] federate learning [14]...
It helps in identifying system failures and security breaches in complex networks of IoT devices. [18] The methods must manage real-time data, diverse device types, and scale effectively. Garbe et al. [ 19 ] have introduced a multi-stage anomaly detection framework that improves upon traditional methods by incorporating spatial clustering ...