Edge-Cognitive Computing for Improvising the Healthcare 5.0

Edge-Cognitive Computing for Improvising the Healthcare 5.0

DOI: 10.4018/978-1-6684-8913-0.ch016
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Abstract

Cognitive business processing must be gradually implemented in the modern world. Cognitive computing software uses machine learning and pattern analysis to simulate reasoning, deduction, learning, and perception. Cognitive computing simulates human intelligence with AI and signal processing. It aids human-computer interaction, natural language processing, speech and image recognition, and HCI machine learning. Hospital and healthcare management systems can track pandemics and diseases using social media data. Cognitive computing in healthcare improves disease management and patient outcomes. The healthcare applications of cognitive computing for the benefit of the large community. Stable network and cloud infrastructures enable cognitive computing's machine-learning problem-solving. The unique qualities of advanced technology can improve medical care. Recursive analysis of unstructured data like X-ray images and computed axial tomography scans has advanced clinical diagnosis through statistics. DNA sequence classification also has infinite permutations due to its complexity.
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Introduction

By facilitating the digitalization of several operations and procedures like water distribution, maintenance services, or advanced manufacturing, IoT can assist in opening the door to the resource efficiency and to an extra sustainable environment. Despite their incredible potential for the deep transformation to sustainability, IoT technologies and frameworks like edge computing are not yet making a contribution to the environmental sustainability of the IoT sector (Adel, 2022). Actually, this industry consumes a lot of energy during the production, operation, and recycling phases, and uses a lot of best quality raw materials in the process. However, the emergence of Edge Intelligent Machines (Edge AI), that also enforces the utilization of additional energy, directly conflicts with the Environmental friendly ecosystem using the eco-IoT paradigm's sustainable vision to reduce these carbon footprints.

Figure 1.

Edge-AIG-IoT main area and their digital circular life cycle

978-1-6684-8913-0.ch016.f01
(Maddikunta et al., 2022)

The technical visionaries think Industry 5.0 will introduce humanity back to manufacturing. Industry 5.0 will combine human critical thinking with high-speed, accurate machines. Industry 5.0's mass personalization allows customers to choose products that suit their tastes. Industry 5.0 will improve manufacturing efficiency and enable human-machine interaction and constant monitoring. Human-machine collaboration increases production quickly. Industry 5.0 can upsurge creation by transfer repetitive tasks to machines/ robots and critical thinking tasks to humans (Lasi et al., 2014).

Since intellectuals use machines, Industry 5.0 creates more skilled jobs than Industry 4.0. Industry 5.0 emphasizes mass customization with human-guided robots. Industry 4.0 uses robots for large-scale production, while Industry 5.0 prioritizes consumer satisfaction. Industry 4.0 emphasizes CPS communication links, while Industry 5.0 integrates Industry 4.0 application areas with collaborative robots (cobots) (Priya et al., 2021). Industry 5.0 offers greener solutions than previous industrial transformations, which did not prioritize environmental protection. Industry 5.0 models use predictive modeling and able to operate intellectual ability to make more accurate and stable decisions. Real-time data from machines and well-equipped specialists will automate most of the process of production in Industry 5.0. Numerous works start debating enabling technologies, applications, and challenges of Industry 4.0 and its representing advanced manufacturing innovations.

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