Smart Systems for Industrial Applications. Группа авторов
Figure 1.7 AI-enabled WBAN architecture.
1.4.4 Medical Applications
WBAN technology improves the efficiency of the activities from patient to doctor, like monitoring the patient’s health regularly and notifications or emergency calling in a flexible way. It offers automatic medical services through remote monitoring of the patient’s vital parameters. All the information is stored from the control unit. It helps the patient to stay at home and get continuous support remotely. In case of any emergency, the sensors implanted in the patient’s body raises the alarm of urgent notification, which will be notified by nearby healthcare provides healthcare services over a distance with the help of communication technology. This can be done by online video consultation with doctors, the transmission of reports and images, and remote medical diagnosis. E-prescription is provided after monitoring the patient’s health conditions. Pulse oximeters are used to measure the amount of oxygen level in the blood bypassing the beam of red and infrared into the human body. Color differentiation is the fundamental concept of oximeters; oxygenated blood is more red, where deoxygenated is purple-blue.
1.4.5 Nonmedical Applications
In non-medical applications, WBAN is used in sports where devices can be wearable. It is effective to monitor the physiological activities of the wearer like heart rate, temperature, blood pressure, and posture of any attitude in sports. Navigation, timer, and distance can also be measured with the help of WBAN sensors.
1.4.6 Challenges
Medical sensors are used to monitor a patient’s body continually and collect information so they should be active all the time; hence energy consumption is high. In body communication, sensors are implanted in vital areas of the body, so if the batteries are consumed fully, the patient has to undergo body surgery to replace a new one. Since the collection of data requires more energy than sending data through wireless time out Mac protocol, which is used in WBAN. Transmission of data is affected by jamming, bit error rate, and link quality. This can be minimized by using Cooperate Network Coding (CNC) since it does not require any retransmission when there is any failure in any of the nodes.
Table 1.4 Role of AI in wireless body area networks.
| Source | Subject matter | Applications | Role of WBAN |
| [21] | Impact of MEMS in WBAN | Personal health monitoring | Wearable WBAN ◦ Assessing soldier fatigue and battle readiness ◦ Aiding professional and amateur sport training Implant WBANCardiovascular diseases ◦ Cancer detection |
| [22–24] | Wireless Healthcare | Health monitoring devicesWearable devices (computer) | Collects multi-physiological information for diagnosing, monitoring the health |
| [25] | Privacy and security in remote health monitoring | TinySecBiometricsBluetooth and Zigbee security servicesWireless security protocols | Link layer encryption and authentication of data in biomedical sensor networksEmploys self-body as a way to manage cryptographic keys for sensorsLogical Link Control and Adaptation (L2CAP) provide improved QoS. |
The major challenge is the security and privacy of the patient’s medical information. Data confidentiality should be maintained to avoid unauthorized access. So, to make sure that the data is sent by appropriate user authentication is necessary. It is also essential to see that received data is not manipulated so that data must be protected for proper medical diagnosis.
The applications and impact of WBAN in healthcare are summarized in Table 1.4.
1.5 AI-Driven IoT Device Communication Technologies and Healthcare Applications
Healthcare providers around the world are a huge source of data, starting from patient history to drug trials. With digitization as a backdrop, many of these records are converted into electronic forms enhancing its utility and enabling vital care decisions. This data has innumerable applications like reviewing the past, understanding the current, and helping predict future trends in the healthcare of patients. AI algorithms, when paired with healthcare data, can drive remarkable insights into intelligent reasoning, quicker analysis of data, provide informed acumen into patient’s healthcare and even extend into decisions on investments in healthcare infrastructure.
1.5.1 AI’s and IoT’s Role in Healthcare
The rise in the Internet of Things (IoT) has enabled two things—monitoring and broader reach of patient healthcare. Devices are interconnected while they remotely manage healthcare equipment. They not only update the individual patient record but also act as a source for AI-driven healthcare analytics at large. Wearable healthcare devices have seen a rise in recent years owing to the popularity of healthier living. Automated at home healthcare management and monitoring chronic conditions have been the other key drivers in the surge of IoT. In a way, it aids practitioners in making well-informed decisions resulting in quicker diagnosis for effective treatment. Thus, increasing innovations in wearable devices like insulin monitors to portable blood pressure monitors, and it is ever-expanding. Advances in healthcare have made it feasible for an emerging field like Remote Healthcare Management [26]. Key attributes to the possible success of Remote Healthcare Management are as follows.
1.5.2 Creating Efficient Communication Framework for Remote Healthcare Management
Patients to rehabilitate at home are a common condition post-treatments or part of a few during which there is a possibility of relapse due to inadequate care. In today’s scenario, patients are provided with AI-powered wearable technology that enables remote monitoring once they have been discharged or in cases where equipment supports is required for treating them. It brings about significant benefits like early warnings of deterioration in patients to allow targeted interventions, also minimize administrative ordeal of hospitalization and readmission. A quick response to any fluctuation in health conditions is made feasible with IoT. Therefore, remote monitoring services become dependable round the clock.
Sensors used in IoT devices are linked together yet separately identified over a communication infrastructure [27]. IoT has three layers of communication: sensors that have the physical interface. This system provides connectivity and server where all the sensory data is stored and processed, as shown in Figure 1.8. The first two layers are simple and can be very cost-effective and predominately setup at the patient’s end. The third layer is traditionally a cloud where an array of services is provided with the help of AI algorithms performance big data analytics. The cloud layer is interconnected with local layers through the multi-hop network,