Challenges and opportunities for enhanced patient care with mobile robots in healthcare

Abstract

Mobile robots are being used more frequently in healthcare environments to tackle a variety of issues, such as patient monitoring, drug administration, and support for healthcare professionals. However, considering how nascent the topic of deploying mobile robots in healthcare is, there hasn’t been much investigation into the potential benefits and drawbacks of doing so. The goal of this research study is to examine the current state of mobile robots in healthcare, the opportunities they present for enhancing patient care, and the difficulties that must be solved to take advantage of these advantages, including safety concerns, dependability and accuracy issues, and cost effectiveness issues. We identify critical elements that support the successful integration of mobile robots into healthcare environments, as well as potential drawbacks and ethical concerns such as patient privacy, informed consent, autonomy, and accountability related to their use, through a systematic review of the literature of mobile robot implementations in healthcare. Our results show the potential of mobile robots to enhance patient care by delivering more effective and efficient healthcare services, but they also emphasize the need for additional research and development to overcome the difficulties in integrating these robots into healthcare workflows. In the end, this research intends to provide a basis for future research and development in this fascinating and quickly developing sector, as well as to contribute to a better understanding of the opportunities and constraints connected with the use of mobile robots in healthcare.

A Review of Digital Transformation and Industry 4.0 in Supply Chain Management for Small and Medium-sized Enterprises

“…Big data analytics is critical in SCM for exploiting the quantity of data supplied by IoT devices and other sources. Organizations can obtain deeper insights into demand patterns, market trends, and supplier performance by processing and analyzing massive datasets [33]. Predictive analytics, a subset of big data analytics, enables supply chain managers to anticipate interruptions, optimize inventory levels, and improve resource allocation [34].…”