An IoT-Based Road Bridge Health Monitoring and Warning System.

Recent earthquakes worldwide have led to significant loss of life and structural damage to infrastructure, especially road bridges. Existing bridge monitoring systems have limitations, including restricted detection capabilities, subjectivity, human error, labor-intensive inspections, limited access to remote areas, and high costs. Aging infrastructures pose a critical concern for organizations and government funding policies, showing signs of decay and impending structural failure. To address these challenges, this research proposes an IoT-based bridge health status monitoring and warning system that is wireless, low-cost, durable, and user-friendly. The proposed system builds upon engineering standards and guidelines to classify bridge health status into categories ranging from excellent to collapse condition. It incorporates deflection, vibration, temperature, humidity, and infrared sensors, combined with IoT and a fuzzy logic algorithm. The primary objective is to reduce bridge maintenance costs, extend lifespans, and enhance transportation safety through an early warning system via a mobile application. Additionally, a Google Maps interface has been developed to display bridge conditions along with real-time traffic video. To validate the proposed system, a 3-D prototype model was constructed and tested. Practical testing of the fuzzy logic algorithm aligned with the simulation outcomes, demonstrating expected accuracy in determining bridge health status.

An IoT Machine Learning-Based Mobile Sensors Unit for Visually Impaired People.

Visually impaired people face many challenges that limit their ability to perform daily tasks and interact with the surrounding world. Navigating around places is one of the biggest challenges that face visually impaired people, especially those with complete loss of vision. As the Internet of Things (IoT) concept starts to play a major role in smart cities applications, visually impaired people can be one of the benefitted clients. In this paper, we propose a smart IoT-based mobile sensors unit that can be attached to an off-the-shelf cane, hereafter a smart cane, to facilitate independent movement for visually impaired people. The proposed mobile sensors unit consists of a six-axis accelerometer/gyro, ultrasonic sensors, GPS sensor, cameras, a digital motion processor and a single credit-card-sized single-board microcomputer. The unit is used to collect information about the cane user and the surrounding obstacles while on the move. An embedded machine learning algorithm is developed and stored in the microcomputer memory to identify the detected obstacles and alarm the user about their nature. In addition, in case of emergencies such as a cane fall, the unit alerts the cane user and their guardian. Moreover, a mobile application is developed to be used by the guardian to track the cane user via Google Maps using a mobile handset to ensure safety. To validate the system, a prototype was developed and tested.

A fuzzy logic-based warning system for patients classification.

Typically acute deterioration in sick people is preceded by subtle changes in the physiological parameters such as pulse and blood pressure. The Modified Early Warning Score is a scoring system developed to assist hospital staff in gauging these physiological changes and identifying patients in need of urgent medical care to avoid catastrophic deterioration. This work discusses the design and implementation of an equivalent warning system that utilizes fuzzy logic techniques to categorize patients' status. The system is implemented and tested in Rashid Centre for Diabetes and Research in UAE. Results are compared with those obtained using the Modified Early Warning System that is currently used in practice. We demonstrate that the implemented system provides reliable results that are in agreement with the current Modified Early Warning Score system, with the added benefit of a scoring scheme that provides a better insight into the status or medical condition of each patient.

Remote patient monitoring and information system.

This paper presents a remote healthcare patient monitoring system, called the Virtual Eye (VI), that utilises the World Wide Web infrastructure to monitor, collect, analyse and record patients' health status. The data is stored in the hospital database and can be accessed from anywhere through the internet. When a patient is in an alarming situation, the VI sends SMS messages to the mobile of the designated health personnel via the public GSM network. The novelty of the system lies in its security and its ability to use both the internet and the GSM network as communication media. Doctors can access the database server to compare the patient's current status with his/her medical history. It can be used by one physician to monitor a group of patients simultaneously, or by a group of physicians who all monitor the same patient. It allows plug-and-play of multivendor off-the-shelf hardware devices, thus avoiding proprietary standards.

A cyber medical center.

This paper describes the design and implementation of a Cyber Medical Center (CMC) using web technology. The intention is to overcome the inefficiency of the traditional filing system for patients' medical records, which are considered to be time and space consuming. Another objective is to enhance the interaction between the user - the patient in this case - and the medical center personnel - the doctors and staff. This task is achieved by developing a cyber medical center interfaced with the Internet to provide direct public access. The traditional filing system is replaced by a database system for maintaining the electronic medical records of all patients in the medical center. The doctors or staff can either view the medical records or update them through the Intranet/Internet. This system has been successfully developed, implemented and tested on the Intranet platform. It will be available in a university medical center for practical use.