It has been announced that smart appliances could stop working properly after just two years because manufacturers are failing to provide tech updates.
According to research from Which?, products such as expensive dishwashers, TVs, and washing machines, which might be expected to last more than a decade, are being abandoned by brands. A lack of software support from firms means devices do not get updated.
When it comes to developing smart appliances in the healthcare sector, data-related issues need attention.
Ravinder Dahiya, IEEE fellow and professor of electronics and nanoengineering at University of Glasgow comments:
“In healthcare, smart appliances can be used to check the lung functions of those with respiratory conditions such as asthma. Although a centralised cloud system has traditionally been used for data management, processing, and storage, it has two major problems. The first is latency to process data and the second is this data creating a significant load on the overall network performance. With the advancement of wearable tech, the advancement of security and privacy is also vital. Currently, there is no unified solution to cover all threats with wearable technology security.
“The energy source for continuous operation is another challenge common to both wearables and smart tech, particularly when they are to be used in low resource settings. Energy efficiency is a critical constraint of wearables due to their small form factor and portability requirements, which prevent them from using large batteries. Low-power devices or on-board energy harvesting devices could help address energy needs.
“Several advanced functionalities are being added to wearable devices to enable new services and target new use cases. However, they are still to be executed on tiny and resource-constrained devices. As a result, more features may result in increased energy consumption, which often compromises the quality of the final wearable applications. Hence, energy consumption is considered as one of the most critical challenges in wearable computing.
“Despite the benefits, wearable sensors such as smart bandages are incredibly technical devices which require a huge amount of data, and therefore do not always provide conclusive outcomes. AI and data analytics based on the inputs from experienced clinicians can help extract useful information from sensory data. In turn, this can help predict the growth of diseases, improvements with diagnosis or even prevent a disease completely by predicting in advance.”
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