Team 5- Presentation Reflections

Group 5

The projects that were presented focused on General Intelligent building themes and methods. The overarching theme of the presentations were the availability of IB methods and how these methods can be implemented. Our projects varied in the target audience, for example Sarina and Alyssia’s project would be helpful to homeowners while Jordan’s can be implement into warehouses and has more of a commercial appeal. As a team we learned about how and why these new technologies can be implemented and got a basic understanding of the numerous advantages that are associated with Intelligent Building technologies. In conclusion, the projects in our group all focused on different usages but showcases the importance of Intelligent Building technologies/ concepts moving forward.

We chose Jordan’s presentation on Robots in Archival Spaces to be presented to the class.

B5 - Object Oriented Database - Marino

Object-Oriented Database

Object-oriented database is a database management system that represents its information in the form of objects. Object oriented database, which is also known as object oriented database management system (OODBMS), similar to object oriented programming languages. It can allow the user to combine the features of relational model such as transaction, concurrency, recovery into object oriented database model. There are three different features of object oriented database such as polymorphism, inheritance, and encapsulation. Polymorphism is known as object oriented programing language. It has ability to process objects according to their data type or class. Inheritance is one of the features of OODBMS that can create a new object from an existing object including all the characteristics of the existing object. Encapsulation is called one of the principal concepts in object oriented programming (OOP). It binds and manipulate the data and functions together as one unit.

The benefits of object-oriented database are composite objects and relationships, class hierarchy, no query language, no impedance mismatch, no primary keys, and one data model. One of the greatest benefits of using an OODBMS is that the user can store many different types of objects in a large class where it can also hold many medium classes as well as many smaller classes or objects. Object oriented database delivers information in a form of class hierarchy, which presents the information that easy to understand without spending too much time to get to know the details. Another benefit of object oriented database is easy to use and it does not have primary key. The user also can store or manipulate the information without spending too much time to mapping tables to objects and back unlike the rational database management system.

The downsides of the object oriented database are schema changes, language dependence. In OODBMS it is difficult to modify, update, or create the schema after completing the database management system. Usually the user has to recompile the system when the user decides to make schema changes. Another disadvantage of OODBMS is selecting the language has to only come from specific language using a specific API which also known as application language independent. This can be very confusing for some users when they are not familiar with API language.

Source: 

"AN EXPLORATION OF." Why Arent You Using An Object Oriented Database Management System? Accessed February 13, 2018. http://www.25hoursaday.com/whyarentyouusinganoodbms.html.

Object Based Databases Tutorial. Accessed February 13, 2018. http://www.tutorialride.com/object-based-databases/object-based-databases-tutorial.htm.

Beal, Vangie. "Polymorphism." What is Polymorphism? Webopedia Definition. Accessed February 13, 2018. https://www.webopedia.com/TERM/P/polymorphism.html.

"OOP Concept for Beginners: What is Encapsulation." Stackify. December 01, 2017. Accessed February 13, 2018. https://stackify.com/oop-concept-for-beginners-what-is-encapsulation/.

http://pi3.informatik.uni-mannheim.de/~tneumann/oodb.pdf

Deutsch,

You did such a great job explaining Rational Database Theory! I like how first you explained the general theory about database and then you went into details explaining the concepts of Rational Database. When I was reading about object oriented database in few articles I also found some interesting information about Rational Database. One of the interesting concept of rational database that I found was the user can modify, update, or change any information that already put in the table. In object oriented database it is difficult for the user to make a change on the database once its management system is completed.

Thomas,

You explained the importance of the SQL very well. I took INFO 210 and this course was about SQL. The database program such as Oracle SQL was interesting to learn but it required a lot of attention in class and practice the program at home in order to master the program. I agree with you that SQL allow us to understand and access the database elements a lot easier compare to some other database program such as Codasyl database.  

Zac,

I felt like I had to make a comment on your post after I read the word “Primavera P6” in the first sentence of your second paragraph. I had experienced using Primavera P6 when I took one of the construction management courses. The course was really fun and it was interesting to use Primavera to make a work schedule of a construction project the fact that it’s not only easy to use to conduct a work schedule but it also shows the Critical path of the project. I personally would like to recommend you to learn about the program if you are interested in learning about scheduling database.

Odorizzi: Current Thoughts on Term Project

This is going to be a very broad post about my current thoughts on a project topic. I am hovering between three of the large topics: BIM, A.I. and sensors.

The case for BIM: I am familiar with Revit, and it is seemingly the most practical and relevant topic because I will use Revit in industry. Hence - it may be good to build a deeper understanding of manipulating a Revit model. For example, it would be nice to build from scratch a Revit model that contains a complete architectural, structural, and HVAC model (like it is done in the real world). But I’ve never done HVAC in Revit before - so that would be a lot to chew.

The case for A.I.: I am very interested neural networks and how they work… and I’m getting acquainted with Bixby, but this does not have the same degree of applicability as the others.

The case for sensors: I think it would be interesting to dive into some of the surveying equipment that I have used out in the field. The first tools that come to mind are investigating exactly how a laser tape works, or there are drill bits that will measure the resistance when drilled into wood to deem whether the wood is rotted or not. It would be interesting to learn how these work and how their accuracy is established.

Group E Post - Education

With the new technologies that available to workers, universities can begin to teach students the coding process that goes into making machines rather than teaching just civil or architectural engineering and computer science.  The education would be much more in depth on AI and robotics, but a student would still need the CIVE or AE background in order to understand the building process. Project based instruction would become more practical: a design could be made and implemented and tested in a laboratory setting.

Odorizzi: Impact of A.I. and Robotics on Safety in Construction Industry

I could envision A.I. having a prevalent impact on all stages of the construction industry.

In design phases, coded computers are already programmed to identify code violations. I could easily see A.I. becoming a virtual presence that guides designers through schemes of a building. Maybe a structural engineer develops a schematic design, but fails to realize that the safety factors for the region of the building are more stringent. A.I. could flag the problem and potentially solve it autonomously.

For construction, I think cameras could be used for A.I. to monitor and identify action being taken by construction workers that could be deemed dangerous, and direct the workers to resolve their situation. The use of robots inherently would eliminate that risk entirely. When cranes and machinery can all be remotely controlled (VR maybe), and humans don’t even need to be on site, that would be the safest for humans… but is also a scary thought.

The Implications of AI in Education - Lauren Kujawa

I think individuals need to be made aware of AI, however I do not think individuals need a full scale education on AI (unless it is their intended career).  I understand that AI is the future of the technology industry, but I think it will take some people time to accept and adapt to AI.  I do not think education will drastically change because of AI anytime soon, but maybe in the future.  

Nay Ye Oo - Implications of AI & Robotics in our World for Safety

Implications of AI and Robotics in our World for Safety

Using AI/Robotics for 'Safety' for human beings can vary from replacing physical labor to virtual cyber security. The first thing that comes to mind for safety is putting people away from physical harm. An example would be performing a task for instance in a construction site that is either dangerous/risky or physically demanding for a human to execute.

Andrew Maita - Cost Implications

Implications for the cost of implementing more AI can have both positive and negative affects on the current system used today. In the long run, replacing, say a car assembly factory, with all automated AI would be cheaper and more efficient in the long run as the need to pay human workers and human error goes away. In the short term, the initial installation and manufacturing of these AI robots could be expensive until the production of these robots becomes cheaper in the future.

Thach-AI Education

I believe that there needs to be a proper teaching on the fundamentals of the Artificial Intelligence so that there is a certain level of universal understanding. AI's technology is far more advanced than any other technology out there so there needs to be a way to teach people what the general aspects of AI are. I think this would help settle some of the fears that are associated with AI and it can show people the advantages that AI has.

Mark O - B1 Post

AI:

Wilson, Jim and Metz, Cade. “Busting the Myths about A.I. Invading Our Lives.” The New York Times. 2017 Dec. 13.

<https://www.nytimes.com/2017/12/13/technology/personaltech/busting-myths-ai.html>

I was attracted to this article based on the title - my mind instantly associates A.I. with robots gradually outsmarting humans and taking over the planet. Hence, it is refreshing to read a NY Times article assuring that the dawn of the A.I. anarchy will not be occurring soon. The article is written as a question and answer with a technology reporter, Cade Metz, who is located in San Francisco and reflecting on the tech/A.I. that he uses and has written about. Metz marvels at the advances in the voice assistants in the past five years, but his ultimate conclusion is that “the improvements have been enormous. But there is still a very long way to go.” He discusses that the goal of voice assistants to understand conversational speech, and the current assistants do a decent job at recognizing speech, but not understanding. With regard to visual A.I., Metz discusses that computer vision techniques can be flawed in recognition which is problematic if A.I. is to be used for security cameras or autonomous cars. As opposed to my initial fears of robot overlords (which is discussed in the article to a degree), the issue that Metz presses to be more urgent is the shift in job markets that will result from automation. We saw an example of this in class with the masonry-laying robot. However, what scares me most about A.I. ebbing into the workforce is the prospect of A.I. overtaking design positions. Structural engineers rely more and more heavily on structural analysis software, and although it is years away from fruition, the thought of software autonomously producing a complete set of design documents seems plausible to me and is very unnerving. I do not believe the construction industry will reach a point where A.I. is trusted enough to stamp and send out a set of drawings, but I do think A.I. will progress to the point of completing and detailing an entire design autonomously.

Computer:

Wod, Marcus.  “The Plan to Build a Skyscraper that Doesn’t Cast a Shadow.”  Wired.com.n  2015 Mar. 13.

<https://www.wired.com/2015/03/plan-build-skyscraper-doesnt-cast-shadow/>

Without saying, computers have become a stable in nearly all applications, especially in the field of engineering. Under the computer tag, an article was listed that discusses the design of a building that will reflect light in such a way to minimize/eliminate its shadow. What I found most impressive in the article is that the architects simply entered their desired restraints into a software, such as building area and maximized light to the ground. In turn, the software iteratetd through all the possible outcomes and spat out the viable shapes that satisfy the restraints. Design at the press of a button! I think this example shows the immense power that computers hold in crafting solutions to particular problems, especially with buildings.

Software:

Tanz, Jason.  “Andy Rubin Unleashed Android on the World. Now Watch Him Do the Same with AI.”  Wired.com. 2016 Feb. 09.

<https://www.wired.com/2016/02/android-inventor-andy-rubin-playground-artificial-intelligence/#slide-7>

Andy Rubin is an incredible developer who created Android and headed Google’s mobile internet efforts, until he left Google to start his own company. Tanz’s article largely recounts Rubin’s constant innovation and unwavering determination to bring his visions of the future into the realities of today. One of the more eye-catching aspects of the article to me was the included timeline that cites Rubin to be pioneering preliminary versions of social networking (1981), mobile phones (1992), self-driving cars (2004) all before the research and development of these technologies were mainstream. As the article calls him, he is an impatient futurist. Pairing with the discussion of AI above, Rubin foresees A.I. being the focus of the next technological era. However, Rubin is aiming to build his neural network database differently than the other tech players. His vision is to send a fleet of robots (sensing machines) out in the world to feed his A.I. database firsthand with immersive data. To do this, Rubin’s company, named Playground Global, invites developers to use Playground’s advanced engineering sensors and hardware to fulfill their ideas. With this setup, Rubin can fuel the creativity of other developers while sending his sensors out into the world to build his database of data. I am anxious to see the A.I. that is developed from Rubin’s platforms; his thoughts and goals sound good in theory, but I have yet to be convinced that they will work in reality. Regardless, it was quite interesting to read about a developer with such an excitement and vision for where tech can be in the future.

Future:

Metz, Cade.  “Building A.I. That Can Build A.I.”  The New York Times.  2017 Nov. 05

<https://www.nytimes.com/2017/11/05/technology/machine-learning-artificial-intelligence-ai.html>

In the same A.I. spirit as the other articles, Metz writes about a prospective tool that is in development for the future of A.I. The article states that only 10,000 people in the world have the expertise required to develop A.I. - which is leaving the large tech companies to scramble for qualified developers. Hence, AutoML is a pursuit of some tech giants such as Google. ML is explained in the article to stand for machine learning, which means that AutoML would describe machines that are capable of coding A.I. This does not currently exist. The most prevalent concern discussed with A.I. was the automation of jobs, which would cause a shift the workforce. If AutoML becomes advanced enough, coders would be coding themselves out of a job. I appreciate that Google’s solution to the lack of qualified computer experts is: “we can code computer experts!” - however, coding computers with artificial intelligence to generate more computers with A.I. will propagate into a fleet of self-improving A.I. I find this to cross the line of what should be done with A.I.

Comments:

To Andrew Maita:

Most of the articles I read for this round of posting pertained to A.I., one of which focused on building a sensory database for robots to encounter and understand the world around them. I don’t know too much about the 3D printers used for buildings, but I believe they are typically stationed in one location and set up to print around themselves. I could easily see 3D printers advancing into a mobile system with sensors that allow the system to move around the footprint of the building and print as needed. I also think it will only be a matter of time until we can 3D print all of the materials needed for a complete building - I would not be surprised if eventually we can 3D print the rebar as the machine builds up the concrete.

To Zac Arnold:

Having programs with the ability to identify code violations is super useful in my eyes. I always envision designing my own house one day, but know that I would mess up something with the architectural codes and restraints. To the same effect, I agree with you that avoiding something that is obviously catastrophic in a design seems like an intuitive “decision-making” ability for the software.

As you say in your sociology section, some people welcome the automation and others have reservations. I typically have reservations. I think automation can easily be taken too far. One of the articles about A.I. that I read discussed how Google is aiming to develop A.I. that can program more A.I. I think this level of automation, where coders are coding themselves out of a job, takes automation too far; yet, it is the same effect as automating cars on the street and putting taxi drivers out of a job.

To Jordan Shuster

I agree with you that robotics and automation has the potential displace large quantities of people from their current jobs. As I have posted before, A.I. coders are trying to code computers that are capable of developing more A.I. software (AutoML). In the same effect as eliminating jobs from the unskilled and lower-class workers, programmers are trying to program themselves out of a job. From an objective standpoint, a well-coded software and machine would be the more efficient and economical option for many jobs. If we keep leaning into reliance on machines, I do not know what will happen to the workers who are displaced from their job. Who knows... as A.I. for business applications becomes more prevalent (as you discuss with your Google Cloud ML), perhaps everybody will have the business chops at their disposal to thrive as successful entrepreneurs.

Post 1, Shuyuan Zhang

AI
After reading the latest reviews and news about the developments of artificial intelligent nowadays on Evernote, I am curious about how is it created and how is it works. So I researched this topic and found some basic explanations to help us understand the general principle of AI.

There are several methods to build an AI. They are Deep Learning, Machine Learning and Generative Adversarial Nets (GAN). The GAN is one of the most advanced and popular approaches for complicated tasks. Most of the researchers and practitioners in this field are making efforts to learn and improve this system. A GAN is composed of two major parts—generator and classifier. The generative model is converting random data to true data and the discriminative model is classifying fake data from true data. They are against and competing with each other. At the same time, they are growing together.

For example, if we want to create an AI painter that is able to draw an apple, we will need to start with training two models. The discriminative model will get some initial inputs such as pictures of apples. This will require another developing techniques called Pattern Recognition. It is because there is no two apples are exactly the same and it is impossible for us to input every single apple in the world to our discriminative model. So pattern recognition can help the computer to find the pattern of how an apple looks like. On the other side, our generative model is getting little inputs about apples. For instance, we only tell it that an apple is about 1-3 cubic centimeters and the color is varying from green to red on the chromatogram. And then we can start running it. At the beginning, the generative model will create some ridiculous stuff such as a pure green cubic or a blood red sphere. It will send its work to the discriminative model. The discriminative model could easily claim this data as fake and start up another create- classify loop. After running this loop for billions of times until the discriminative model is deceived by generative model, then we can say that we successfully made an artificial intelligent painter that is better than human artists in some degree.


Database & Future

According to above discussion, I realized that other topics for group E for this assignment are all having some connections. For example, database system is the key components for discriminative model since it is collecting data as the initial inputs for this model. Database system is not only collecting but also organizing and processing raw data that makes the pattern recognition process a lot easier. Network and sociology are providing support to this system from different aspects as well.

[1]Generative Visual Manipulation on the Natural Image Manifold.Jun-Yan Zhu.ECCV 2016.

[2]Generative Adversarial Networks.Goodfellow. 

[3]Unsupervised Representation Learning with Deep Convolutional Generative Adversarial Networks.Alec Radford. [4]Deep multi-scale video prediction beyond mean square error.Michael Mathieu. 

Comment 

Thomas Sisson

I am shocked when I read your MX3D article. I didn’t realize that our 3D printing techniques are so mature and advanced that it can be used in construction filed in real life. And I agree with you that this can push the boundaries of conventional concrete to be used in projects that are more architecturally complex in shape. Your work in ‘Future’ session inspired me as well. My post is about AI but I only focused on this technique it self. You mentioned some connections between AI and our field that makes me start to think this way.

Dee Dee Strohl

Your article about HVAC & Sensor is interesting. It is a convenient way to manage your house/ office and can effectively increase equipment’s efficiency. I am thinking in the future, if most of buildings are having sensor system installed and AI technique is mature enough. We don’t even need an app to manage this system by ourselves. HVAC equipment with AI will finish all of the work for us and a great amount of energy will be saved. Both of our energy and environment problems will be mitigated.

Milligan

I like the video about software you posted. Before I watch that and read your discussion, I thought we only use software in the design phase behind a computer. But with the development of mobile devices, we are able to use apps during construction phase on filed. This can make the project manager or construction engineer perform their work in a more safety and effective way.