Deciosn science

MCIS6123 Decision Science (Prof. Maull) / Spring 2022 / HW0 This assignment is worth up to 20 POINTS to your grade total if you complete it on time.

Points Possible Due Date Time Commitment (estimated)

20 Monday, Feb. 28 @ Midnight up to 8 hours

• GRADING: Grading will be aligned with the completeness of the objectives.

• INDEPENDENT WORK: Copying, cheating, plagiarism and academic dishonesty are not tolerated by University or course policy. Please see the syllabus for the full departmental and University statement on the academic code of honor.

OBJECTIVES

• Familiarize yourself with the Tableau platform.

• Familiarize yourself with Github and GitLab.

• Listen to a podcast to understand and articulate real world business analytics.

• Read an academic paper and articulate decision making technology innovations in smart agriculture.

WHAT TO TURN IN

Please turn in a copy of a .docx, or .pdf file (Word Document a PDF) to Blackboard with the answers to the questions labeled with the § sign in each objectives section.

ASSIGNMENT TASKS

Part 1 : (0%) Familiarize yourself with the Tableau platform.

Tableau has long been a top platform for analytics. In this assignment you will be asked to create and account on tableau and find some projects on the platform that interest you. I would highly recommend you use your .edu account so that you can actually get some of the student / educational benefits of the platform. We may be coming back to Tableau from time to time in this course, so this account setup is optional, but you may find it useful to setup.

Task Detail

§ There are no questions to answer for this part.

Part 2 : (0%) Familiarize yourself with Github and GitLab.

Github is the de facto home of open source software on the web. Though Github is the platform of choice for many projects, the rising star in the space is Gitlab where there are a lot of open source projects moving there for a variety of reasons. Either way, you should be familiar with both platforms and you are free to open and account in both places, though we will be using Github for this class (very lightly).

If you already have a Github account, you can skip this section.

You will be creating an account on Github for several reasons:

1. we will be using Github to store, transmit and share homework and lecture notes and other materials,

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2. we may use Github for at least one assignment, 3. at some point in your future, you will very likely be using Github/Gitlab, if for private work for a company

or public work on an open source project.

Just like Tableau, sign up with your .edu email, as there are many benefits to doing so!

Task Detail

§ There are no questions to answer for this part.

Part 3 : (20%) Listen to a podcast to understand and articulate real world business analytics.

IoT (Internet of Things) is by now a household term, even if most households do not fully grasp its impact, importance or use in our modern world.

The podcast IoT For All provides up-to-date information about the goings on in the IoT space providing pro- fessionals timely information about trends, technologies and the movers and shakers shaping the future of IoT.

You will listen to the almost half-hour podcast with Wienke Giezeman, CEO and co-Founder of The Things Industries and answer some of the questions below. In this enlightening conversation you should enhance your knowledge of what is going on in the industry and where technologies are likely to trend in the near term.

You will be responsible for listening to the podcast interview in its entirety with an ear towards how this tech- nology will shape businesses, systems, tools end-user experiences and decision making platforms in the future and the systems that promise to provide customer benefits not yet impacted by AI.

Answer the questions below based on the details found in the podcast.

To listen to the ~27 minute podcast at one of these links:

• E155 Integrating IoT in Your Business • on Youtube E155 Integrating IoT in Your Business (video) • on Spotify E155 Integrating IoT in Your Business (audio)

Task Detail

§ Answer the following questions:

1. What are the core tools that Wienke identified as key to the “digital transformation” of businesses? 2. Weinke is in favor of simple versus complex solutions to IoT integration. Why? 3. What is LoRaWAN and how does it fit into the IoT landscape? 4. Why does Weinke thing we’re in the “trough of disillusionment” within IoT right now? 5. What would you say are some challenges in improving decision making strategies with sensor-to-cloud

integration? Draw on your own knowledge, the information we’ve talked about in the lecture and some of the content from this podcast.

Part 4 : (80%) Read an academic paper and articulate decision making technology innovations in smart agriculture.

We are entering a new epoch in technology where the introduction of low-cost sensor technology, AI and IoT (Internet of Things) are converging to provide tools for automated data collection, real-time analysis and im- portantly, high quality decision making.

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You may be aware that the food production economy is an important area where AI and IoT are increasing in their impact, and the emerging field of smart agriculture promises to provide a host of new techniques to optimize growth, land use, yields and distribution.

One side of the complex food economy is the production of animal proteins, and while plant-based diets are becoming more popular for health and ecological reasons, animal protein is still crucial to many diets around the world, yet tremendous pressure on ecological systems can be seen and are thus the focus of intense scientific research. Wild caught animal protein yields are often unpredictable and typically difficult to scale, and so high yield, controllable farming techniques are generally preferred by producers. Furthermore, fish protein is an important production source because space, time and nutrient components can be monitored and controlled in cost-effective, yield-optimizing ways.

Management of these farming processes is a challengeing problem, and ensuring safe, efficient, high quality animal protein is a high priority within the industry and lab alike. The 2021 academic paper by Rashid, et al. IoT based Smart Water Quality Prediction for Biofloc Aquaculture uncovers some of these issues in fish aquaculture and provides interesting insights into how decision sciences are helping develop tools for more predictable, higher quality outputs.

You will read the 2021 paper

Md. Mamunur Rashid, Al-Akhir Nayan, Sabrina Afrin Simi, Joyeta Saha, Md. Obaidur Rahman and Muhammad Golam Kibria, “IoT based Smart Water Quality Prediction for Biofloc Aquacul- ture” International Journal of Advanced Computer Science and Applications(IJACSA), 12(6), 2021. http: //dx.doi.org/10.14569/IJACSA.2021.0120608

and answer the questions below. While there are several errors in this paper it is nonetheless a good intro- duction to the area of aquaculture and exposes some of the regional problems with the technique and how technology may come to bear on better solutions to those problems, and especially how those solutions shape behaviorial/decision responses.

Give yourself an hour or so to read the 7 page paper thoroughly, an hour to brainstorm your writing and another hour or less to write your answers (specified in detail below).

You will be evaluated on the following criteria:

• accuracy of your answers, • thoroughness and detail of your answers, • uniqueness and novelty of your answers, • demonstrated comprehension of the question and active demonstration of acquired conceptual knowl-

edge, • demonstrated comprehension of the material’s relevance to decision science concepts covered so far.

Task Detail

§ You are to carefully read this paper in its entirety and formulate a response to it. Your response should be between 300 and 500 words (approximately ½ to ¾ page of text or about 2-3 paragraphs). You are expected to

• address the major points of the paper, • address why this paper is important, • expand on some of the challenges the authors bring up in the paper — your answer would benefit from an

exploration of problem space of aquaculture and how technology is or is not being used in that business,

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• conclude with a few of your own personal thoughts about the paper, smart farming in general and the use of AI in agri(/aqua)culture — use your own thoughts and ideas in your response, there are no right or wrong answers when expressing your opinion.

Make sure you are brief, to the point, yet thorough in your descriptions and writing.

§ What is biofloc aquaculture?

§ What do the authors’ say were the limitations of the DL contributions of Yang, et al.?

§ What sensors were used in the authors’ test system?

§ According to the authors, how did the “Matshyabid Biofloc Aquaculture Farm” differ from the others?

§ Which of the data parameters collected was used to test against the ML model?

§ Which ML model was used and why did the authors use that model?

§ What do you think could be improved with the output notification given in the app? Answer your question with particular attention to what decision the end user is being asked to make and how they would know that is the right decision or that the result of their decision yielded the desired outcome.

§ [BONUS] This is a bonus question worth up to 5 additional points to your total score. List up to 5 errors you found in the paper – more points will be given for logical, methodological or scientific errors, or errors made as a result of lack of clarity or presentation.

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