As an example of a real-time location tracking service for patient and hospital asset information, the Mount Sinai Hospital has built a real-time location system (RTLS) infrastructure that tracks assets including personnel, monitors appropriate utilization levels, optimizing the productivity of medical staff. The hardware used for RTLS includes asset tags, autoclave tags, temperature monitoring tags, patient tracking tags, locators, transmitters, and receivers. As software, the RTLS uses location tracking applications and reporting applications, which visualize the current monitoring status on a dashboard. The previous system cost about US $1,729 per shift to locate medical devices in 26 wards, but the application of the IoT service has reduced the cost requirement for managing patient and hospital assets by about US $1.26 million per year. At Aventura Hospital in Florida, USA, hospitalization time was reduced by 3,000 hours over 9 months by using the RTLS technology, which allowed the hospital to operate more than 400 additional rooms. Thus, the RTLS was able to achieve efficiency in asset management and personnel input, enabling medical services to be provided in a timely manner for positive patient experiences [2,16,17].

Yongin Severance Hospital has been seeking to transform into a smart hospital by establishing a digital component of the hospital through the involvement of medical IT experts, biomedical engineering experts, and statistics experts. In the event of an infection or emergency, location information can be monitored in the hospital’s Integration & Response Space through an infection tracking RTLS solution. This system was able to overcome the limitations of existing infection tracking, which previously relied only on oral reports and CCTVs. Furthermore, movement routes of hospital workers, patients, and caregivers and density in the hospital could be identified based on real-time monitoring of location information, allowing the hospital to predict the time and place of overcrowding and implement preemptive responses [17] (Figure 2).

Sana Klinikum, a German medical corporation, adopted a real-time bed location identification system using Simplinic GmbH, an IoT cloud solution. Using beds equipped with pressure sensors from Stiegelmeyer, the system collects information about the occupancy and location of individual beds in medical institutions. By measuring the patient’s body pressure on the bed and transmitting a bed occupancy signal through Bluetooth, information on the occupancy and location of each bed can be obtained. This automated process has shortened the time required to search for beds, thereby reducing the burden on medical personnel [18] (Figure 3).

Hazel Hawkins Memorial Hospital in the United States uses temperature and humidity sensors to maintain a sterile environment in operating rooms. In operating rooms, an appropriate temperature of 18°C–24°C and an appropriate humidity of 50%–55% should be maintained to prevent the growth of microorganisms, and to maintain body temperature to obviate the risk of infection during surgery. In the past, such information was manually recorded to maintain proper temperature and humidity conditions. However, temperature and humidity records were missing during periods when there were no scheduled operations, making it impossible to generate continuous data. To compensate for this shortcoming, monitoring sensors and wireless environmental sensors were deployed to collect data on humidity, temperature, positive pressure, and refrigerator temperature for 24 hours a day. This system has made it possible to create an ideal operating room environment, where the growth of microorganisms is inhibited and electrostatic discharge is prevented [19] (Figure 4).

Soonchunhyang University Bucheon Hospital adopted a smart indoor air quality improvement service (known as the “SMART IoT Good Air Service”) that measures and intensively controls indoor air quality. Real-time IoT environmental sensors collect and transmit measurement data on indoor air pollutants such as ultrafine dust, fine dust, volatile harmful substances, and carbon dioxide, and on outdoor air pollutants such as ozone, carbon monoxide, nitrogen dioxide, and sulfur dioxide. The results are presented to visitors as graphs in real-time. By applying air quality monitoring sensors to medical services and managing the air quality of the respiratory allergy center ward, the hospital provides a safe and comfortable treatment space to patients with respiratory and lung diseases [20,21] (Figure 5).

At Royal Adelaide Hospital in Australia, an IoT system was introduced to efficiently manage the energy consumed within 24-hour periods to provide medical services such as the management of medical devices, lighting, and the operation of ventilation systems. The hospital collects energy consumption information measured from various IoT devices such as temperature sensors, power meters, circuit breakers, and uninterruptible power supply devices. The collected information is transmitted to the analysis/control system to analyze energy usage patterns. The analyzed data are used to manage the amount of energy consumption and improve the efficiency of energy consumption. The system has reduced hospital operating costs, and the saved costs are used to improve the treatment environment, eventually leading to improvements in the medical services provided by the hospital [22].

Catholic Kwandong University International St. Mary’s Hospital has been using various IoT technologies to reduce energy consumption in hospitals. To reduce energy consumption, which amounts to about 2.5 times that of a university (30 kilograms of oil equivalent [kgoe]/m²) and 1.7 times that of a large company (43 kgoe/m²), the hospital introduced IoT services to measure energy consumption and environmental variables. By collecting environmental and energy data in real-time through temperature and humidity IoT sensors in operating rooms, emergency rooms, and intensive care units, where environmental management is important, appropriate responses can be made if abnormal signs are detected. Smart plugs manage the energy usage of medical devices that consume a lot of power (e.g., magnetic resonance imaging and computed tomography devices), and consumption-related data from the plug-in wireless communication module are transmitted to the server to analyze energy use [23,24].

The Smart Health Service frequently measures the blood glucose levels of patients with diabetes to prevent acute changes in the glucose level. Most existing blood glucose measurement methods are based on direct measurements of the blood glucose concentration in a blood sample. The existing measurement methods using blood samples cause physical and psychological pain to patients due to the need for regular examinations. These methods also place a burden on medical service providers in terms of workload and risk of infection exposure. To preclude medical staff ‘s risk of infection caused by repeated blood glucose measurements in patients with diabetes and to ensure work efficiency, Montefiore Medical Center in the United States introduced real-time blood glucose meters that provide data obtained from a blood glucose measurement sensor. A real-time blood glucose meter is a device that can continuously measure blood glucose levels after a sensor is inserted once. The hospital offered this option to patients who needed to control their blood glucose levels after being admitted to the intensive care unit due to coronavirus disease 2019 (COVID-19) infections. The use of the real-time blood glucose meter reduced the number of point-of-care examinations by up to 60% among patients who were prescribed continuous insulin infusions, when compared to the use of an invasive blood glucose meter [25–27] (Figure 6).

Veterans Health Service Medical Center, a medical institution dedicated to the COVID-19 response, created a medical environment for effective responses to infectious diseases by utilizing IoT technology for bio-signal measurements. A monitoring and response system using a wearable device sensor was used to measure bio-signals such as the patient’s body temperature, pulse, blood pressure, and oxygen saturation. By minimizing the frequency of contacts between patients and the medical staff, this system could reduce the risk of infection and enable patients’ conditions to be monitored in real-time. If a patient was determined to be at high risk, this information was transmitted to medical staff to facilitate a prompt response. This system also reduced the number of simple repetitive tasks, such as measuring body temperature and blood pressure, thereby improving the work environment and treatment efficiency [28,29] (Figure 7).