Cloud-based WBAN: The next-level wearable system

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  Quantumrun Foresight
• January 31, 2023

Research in wireless body area networks (WBANs)—connected nodes placed throughout the human body—has been growing rapidly. These networks communicate using electromagnetic waves. While WBANs are promising, they have some limitations that slow down performance. Some researchers are looking into tapping the ample storage and computing capacity of the cloud to enhance WBAN connections.

Cloud-based WBAN context

A WBAN is a network that has different sensors, nodes, and actuators. This network is designed to work with the human body and its environment. To ensure a steady data exchange, the network must be very reliable, use little energy, work over a long range (up to 5 meters), be interference-resistant, and work at different transmission speeds. WBANs were first created in the 1990s at the Massachusetts Institute of Technology (MIT) to connect electrical devices to the human body. Since then, scientists have been trying to increase the bandwidth of these devices so they can be used longer while being less invasive. Researchers have also been trying to make these devices cheaper so more people can use them.

While WBANs can be used to provide better medical wearables that can accurately scan and update real-time information, these networks have several significant challenges. They have limited memory, processing, and power resources, meaning energy management is a big roadblock. Long term, the devices need to use less energy so the battery life can be extended. In addition, WBANs need support from the network infrastructure and different software programs, like remote procedures, database processing, and a user interface. Hence, some researchers think that moving these computing- and energy-intensive processes to the cloud can greatly improve the performance of these networks.

Disruptive impact

One of the more interesting research on transitioning WBAN data and processing to the cloud is using blockchain technology to ensure tamper-proof data. WBAN collects a lot of sensitive and personal data, including blood pressure, ECG, body temperature, brain waves, and even blood parameters. The collected information has various applications in industries such as hospitals, schools, government departments, and disease research. However, the problem with WBANs is that they generate vast amounts of data beyond the storage capacity of its sensor nodes. Given this limitation, medical technology engineers are looking to configure WBANs to instantly upload their collected information to the cloud. 

Having data stored in the cloud is convenient, and allows the collected medical data to be accessed by a much larger variety of potential users/stakeholders and processed into a broader variety of applications. However, data transferred to the cloud always generate security concerns. More worrisome, medical information stored on a cloud server may be at a greater risk of being intercepted and tampered with maliciously while uploaded.

Here, medical technology engineers are also exploring the use of blockchain systems to address security concerns, as data on a blockchain can be made traceable, anonymized, and irreplaceable. This technology usually has seven layers: application, contract, incentive, consensus, network, data, and security. These blockchain features, including being distributed and having a consensus mechanism, makes it ideal for security problems like access control and verifying integrity. Medical information processed through this technology will ensure privacy and accuracy, allowing for better doctor-patient relationships.

Applications of cloud-based WBAN

Some applications of cloud-based WBANs may include: 

• More hyper-local data centers located within hospitals and clinics to ensure that cloud-based WBANs have near-zero latency (the time it takes for signal to travel between devices).


• Faster WBAN devices and interfaces that can update nearby hospitals and clinics on potential medical emergencies.


• Data processing that can be traced at every stage, including relevant updates. These features can lead to more secure and accurate electronic health records.


• Doctors heavily relying on WBAN data to accurately diagnose and create treatment plans, which can lead to better patient care.


• The use of AI to scan through WBAN data and detect patterns, including attempts at data manipulation.

Questions to comment on

• If you’re using a WBAN device, what are the benefits and challenges?


• How else can the cloud improve WBANs?