Week 8 Assignment
Question 1
Geospatial analytics offers a broader viewpoint for companies and assists with decision making. Geospatial data lets companies control their activities, attract customers, and make decisions about promotions (Yin, Liu, Padmanabhan, Terstriep, Rush & Wang, 2017). It also directly benefits customers, using advanced sensor technology and global positioning systems mounted on their smartphones. Companies can define the unique needs of consumers and consumer issue locations using geospatial data and trace them back to the goods efficiently. Another example is the telecommunications industry, where geospatial analysis may permit communications companies to collect regular transactions from a network to recognize the geographical areas in which several attempts to connect voice, information, text, or the Internet have failed.
Question 3
Consumer-oriented localization-based analyzes fall into two major categories: (a) GPS navigation and data analysis; (b) historical and current localization market analysis. Consumers benefit from analytical applications in many fields, including fun and wellbeing, as well as improved productivity for their people.
Question 4
Location tracking based profiling is robust; there are many advantages of location profiling tracking; they include business management, friend tracking, emergence purposes, children’s safety, among others. There is the various application on location-based services (LBS) (Yin, Liu, Padmanabhan, Terstriep, Rush & Wang, 2017). they are navigation, sporting, tracking, billing, and marketing. In navigation, it is used to locate the geographical points of the phone using the navigation positioning system to the required place, destination, and vehicle. In sports to work out data like distance and time. This can be collected using data location. Although location-based profiling has some is powerful, it is faced with some privacy issues. A third-party application can track the mobile of phones and individuals, which lead to great problems. Most of the users working on private companies are unaware they are being followed using their phones. The model of sense is built using the information from the mobile companies, which follow each phone as it navigates from one location to another location with the help of GPS.
Exercise 2
MYCIN is an artificial intelligence (AI) program for treating blood infection. Based on the available information, the MYCIN program could attempt to diagnose patients or suggest further tests to be done on a patient. After the recommendation, the program can explain the reasons behind the recommendation. Moreover, the program is based on around 500 production rules, which makes it operate as a competent human specialist in blood infections rather than just a general practitioner. MYCIN worked with a simple inference mechanism and a ~ 600-rule knowledge base. The doctor running the program will be asked about a variety of basic yes/no or terms (Kokol, Zavrsnik & Vosner, 2018). In the end, a roster of potential bacteria ranked between high and low based on the likelihood of each diagnosis. Its confidence in the probability of each diagnosis, the rationale behind each diagnosis (i.e., MYCIN will also list the issues and rules that made the diagnosis rank a specific way), and its prescribed treatment course for medicines.
Knowledge-based AI seems the way to go in the future of medicine. It is the ability to collect information, process, and give the end-user a well-specified performance that distinguishes AI technology from conventional health-care techniques. AI does so by algorithms for machine learning. Such algorithms can recognize behavioral patterns and create their reasoning. AI algorithms must be checked regularly to reduce the error margin.
References
Kokol, P., Završnik, J., & Vošner, H. B. (2018). Artificial intelligence and pediatrics: a synthetic mini-review. arXiv preprint arXiv:1802.06068.
Yin, D., Liu, Y., Padmanabhan, A., Terstriep, J., Rush, J., & Wang, S. (2017). A CyberGIS-Jupyter framework for geospatial analytics at scale. In Proceedings of the Practice and Experience in Advanced Research Computing 2017 on Sustainability, Success, and Impact (pp. 1-8).