Artificial intelligence (AI) refers to the use of machines that mimic human intelligence by thinking and acting has humans would (Frankenfield, 2022, para 1). Within the long-term care sector, AI can allow and improve a number of technologies such as remote monitoring systems, social robots, and virtual assistants that interact daily with elderly residents and their caregivers (Lukkien et al., 2021, para 2). As Lukkien et al explains (2021), it is believed that AI allows these technologies to become familiar with and understand their environment and adapt to changing actions. For example, the use of AI in camera-based monitoring within long-term care facilities can allow those cameras to categorize resident activities such as lying down, sitting, standing, or walking or can estimate the amount of time a resident spends getting in and out of bed and the risks involved with such an activity. Another example Lukkien et al (2021) presents as usefulness of AI in long-term care is in its ability to track, through sensor-based monitoring systems, the walking speed of residents and pinpoint variations in movements indicative of cognitive and functional decline. In turn, AI detection of such declines can quickly alert caregivers of needed care and possibly thwart further decline.
Machine learning is a method of data analysis branching off of artificial intelligence that is based on the concept of systems learning from data, identifying patterns, and making decision with little human intervention (SAS, 2022, para 1). Similar to AI, machine learning can provide insight to doctors and caregivers on change to resident behaviors or actions that could lead to potential injuries or hazards. For example, PruittHealth, a long-term care organization, uses a machine learning tool that utilizes AI and predictive analytics to identify and alert staff of changes to a residents conditions and potential fall risks and, in doing so, PruittHealth reduced the number of fall occurrences among its residents to zero (Wider, 2021, para 1).
Frankenfield, J. (2022). Artificial intelligence: What it is and how it is used. Retrieved from
Lukkien, D., Nap, H., Buimer, H., Peine, A., Boon, W., Ket, J., Minkman, M., & Moors, E. (2021). Toward responsible artificial intelligence in long-term care: A scoping review on practical approaches. Retrieved from
SAS. (2022). Machine learning, what it is and why it matters. Retrieved from
Wider, J. (2021). ML tool reduces number of falls at one long-term care facility. Retrieved from
Topic Option 2 Information Technology and Future Trends within Long Term Care
The Long-Term Care (LTC) industry is facing challenges to address resident feed while delivering assistance in daily events and personal care. Different approaches to services for older adults and LTC are required to tackle these challenges. A potential benefit from current and developing technologies would be a possibility to provide a new person-centered environment in LTC settings. Technological development has contributed to the delivery of high-quality, on-time, acceptable, and affordable healthcare. The use of nanotechnology in medicine can have a significant impact on health by improving the diagnosis, prevention, and treatment of diseases (Hua 2018).The preventative measures taken in the facility can help ease residents stress and reduce residents readmissions into hospitals. Advancements in nanoscience have led to the rise of a new production of nanostructure. For instance, one benefit of the use of nanotechnology is that it improved therapeutic outcomes on patients going through cancer therapy while also reducing the side effects. Future trends will have an impact on the overall LTC delivery options. Technology advancements will allow caregivers to easily provide better care to residents or patients. For instance, caregivers are using computer-based technology to improve the way they monitor and tend to patients. In return, patients and residents are using software-related devices and different applications to have more mobility and a better quality of life. The COVID-19 pandemic has shown troubling weaknesses in the long-term care system, it also displayed how telemedicine can aid nursing home residents and their families (Su 2021). This trend can possibly change how we provide long-term care in the future.
Hua, S., & Wu, S. Y. (2018). Editorial: Advances and Challenges in Nanomedicine.
Frontiers in pharmacology,
Su, Z., Meyer, K., Li, Y., McDonnell, D., Joseph, N. M., Li, X., Du, Y., Advani, S., Cheshmehzangi, A., Ahmad, J., da Veiga, C. P., Chung, R. Y., Wang, J., & Hao, X. (2021). Technology-based interventions for nursing home residents: a systematic review protocol. BMJ open, 11(12), e056142.
Review the contributions and determine if they have any gaps in their understanding of what happens at each layer.. 50-75 words
The Transmission Control Protocol and Internet Protocol Layers refers to the communication protocols that enable use to do anything over the internet. There are four layers. In the Network Interface Layer things like sending information between hosts on the same local network and translating data from higher layers are done. The layer right above that would be the Internet Layer where data is packaged into packets, receive incoming packets of data, and addressing and transmitting packets occur. Then there is the Transport Layer this layer is responsible for end-to-end communication on the network. In short, the transport layer collects message segments from the application and transmits the to the nest layer.
Physical Layer hubs, cables, modems, and repeaters.
Data Link Layer bridges, switches, NICs,
Network Layer routers, brouters
Transport Layer gateways, firewalls,
Application Layer PCs, smartphones, servers
The TCP/IP Protocol suite was developed in the 1960s and recognized throughout the world after 1983. As for the OSI reference model it was also recognized throughout the world in 1983. Some key similarities between the TCP/IP and OSI Model is that they describe how data is transmitted between devices on a network. Both models also divide the networking concepts into layers. The ideas about how data is broken down into smaller pieces and passed from layer to layer is the same as well. Another similarity is that these models are used to troubleshoot various networking problems. Both are modular and each layer represents a separate set of functions and protocols. Some of the ley differences between the two would be that the OSI model is a more elaborated model where each layer has separate functionality. Unlike the TCP IP model, it does not combine any layers. The OSI has 7 layers, and the TCP IP has 4 layers. The TCP/IP model is more geared towards networking hardware and software used on the internet as to the OSI models is more general and can be applied to any type of network.
Ahmad, A. (2022, May 9). Comparison Between TCP/IP and OSI Model. Retrieved from https://afrozahmad.com/blog/tcp-ip-vs-osi-model-differences-and-similarities/
What is the TCP/IP Model? Layers and Protocols Explained. (2020, November 3). Retrieved from FreeCodeCamp: https://www.freecodecamp.org/news/what-is-tcp-ip-layers-and-protocols-explained/