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Design and Implementation of lot devices, Fall, 2020

  • Instructor: Kun-chan Lan
  • Fall 2020, CSIE Room 4202, 14:10~17:00 Monday

 

Nature of this course

An introductory course to teach you how to become a “maker” of Interentof Things (IoT) technology using publicly-available open-sourced tools

Goals:

•A brief walk-through of the open-source tools (both hardware and software) you can use to create an IoT application

•Create your own IoT product at the end of the course

•Your project will be encouraged to compete for IoT-related competition(e.g. FITI or 龍騰)

 

Objectives

•We start with an introduction of various open-sourced tools such as Arduinoand Android

•Product-based learning (PBL)

•Guide you through the cycle from having an  idea to finally creating a real product

•A strong hands-on focus(A homework/project due every 5 weeks)

 

Prerequisite

•Programming knowledge in Java/C++ (should have been covered in your undergraduate junior years)

•iOS/Android programming experiences(will give you example codes for the 1sthomework)

 

Lecture Slides

•week 1 (9/7) Administration issue

•week 2 (9/14) Tutorial for homework (by TA)

•week 3, 4 (9/21, 9/28) Introduction to Arduino and RasberryPi

•week 4, 5, 6, 7, 8 (9/28, 10/5, 10/12, 10/19, 10/26) AI for IoT, Deal with overfittingBack propagation

 

Course Video Link

week 2 (9/14) Tutorial for homework (by TA)

week 3 (9/21) Introduction to Arduino and RasberryPi

week 4 (9/28) Introduction to IoT

week 5 (10/5) Introduction to Deep Learning (I)

week 6 (10/12) Introduction to Deep Learning(II)

week 7 (10/19) Introduction to Deep Learning (III)

week 8 (10/26) Introduction to Deep Learning (IV)

 

Announcement

Date

Content

 

2020/09/04

Please join the "Line" group for the course: Link (Use the smartphone to open)

 
2020/09/07

Use QR code below to check in the class

 

 
2020/09/21

Term project grouping

https://docs.google.com/spreadsheets/d/1Bu3CyFN-3ssIAbHGg3mKOczuH5GvGBcZLnEzbiW1cMs/edit#gid=0

 

 

 

Instructor

Prof. Kun-chan Lan

Office: new CSIE building 12F 65C05

Office hours: 

–15-16pm on Wednesday

–15-16pm on Friday

or by appointment via e-mail

Email:  This email address is being protected from spambots. You need JavaScript enabled to view it.

TEL: +886 6 2757575 ext 62550

 

TA

呂紹樺(Harry)

Office: new CSIE building 5F 65501

Office hours: 14-16pm on Tuesday, or by appointment via email

Email: This email address is being protected from spambots. You need JavaScript enabled to view it.

TEL: 06-2757575 ext.62520(CSIE) ext.2501(LAB)

 

Grading Policy   

•Working as a team (70%)

    –Hardware(20%)

    –Visualization (15%)

    –App (35%)

        --DNN models & Phone UI (28%)

        --Project documents: proposal/codes/demo video (7%)

•Working as an individual (30%)

    –Homework I (15%)

    –Homework II (15%)

•Class participation (up  to +/-10%)

    -In-class discussion

 

Syllabus

•week 1 (9/7) Administration issue

•week 2 (9/14) Tutorial for homework (byTA)

•week 3 (9/21) Introduction to Arduino and RasberryPi

•week 4 (9/28) Introduction to IoT

•week 5 (10/5) Introduction to Deep Learning (I)

•week 6 (10/12) Introduction to Deep Learning(II), Homework I  due

•week 7 (10/19) Introduction to Deep Learning (III)

•week 8 (10/26)Introduction to Deep Learning (IV)

•week 9 (11/2) Proposal discussion , Project proposal due

•week 10 (11/9) Project report (I),

•week 11 (11/16)Project report (II), Homework II due

•week 12 (11/23) Project report(III) Project due (Hardware)

•Week 13 (11/30) Project report(IV)

•week 14 (12/7) Project report(V) Project due (Visualization)

•week 15 (12/14) Project report (VI)

•week 16 (12/21) Project report (VII)

•week 17 (12/28) in-class project demo (Dancing pad); submission of codes/video

 

Homework 1

Measuring pulses with your phone

A. Design a case for beetle 

Please follow this format to hand in your sketchup design via email

Email : This email address is being protected from spambots. You need JavaScript enabled to view it.

Subject :IoT_hw1_3DP_p12345678(student ID)

Your file should include your gcode(not .stl file)

TA will print out the design,and bring it to the next class

B. Arduino and Android code

download code

C. Hand in your homework

A “B”will be given if you can follow step-by-step instructions to complete homework

The more details in your report the more score you get (You can add some graphs)

Please follow this format to hand in your homework via email

Email : This email address is being protected from spambots. You need JavaScript enabled to view it.

Subject :IoT_hw2

File name:IoT_hw2_p12345678(student_ID)

Your file should include your report(.docx) and code(android project)

download report form

Don’t forget! You need to reserve time to demo your work, please make an appointment via this email

D. Demo

Location : new CSIE building 5F, Laboratory for experimental network and system (LENS)

You need to prepare :

  --Smartphone

  --OTG

  --cell phone cable

  --Arduino beetle

  --PPG sensor

After you show TA that it can work, your homework is done

Homework 1 due : 10/12

 

Homework 2

Design a machine learning model for handwriting recognition

A. Hand in your homework

If you didn’t modify the code but submit your report in time, your score will be B

Try to modify the code to get a better accuracy will be a bonus

The more details in your report the more score you get (You can add some graphs)

Please follow this format to hand in your homework via email

Email : This email address is being protected from spambots. You need JavaScript enabled to view it.

Subject :IoT_hw2

File name:IoT_hw2_p12345678(student_ID)

Your file should include your report(.docx) and code(.ipynb)

download report form

download example code

After you send your work, your homework is done

Homework 2 due : 11/16

 

Term Project

A smart insole

A. What you need to deliver in your project

Hardware (20%)

  –An integrated sensor module contains pressure sensor and accelerometer  

  –Nice packing

    --Use of 3D printing

  -Receive data correctly on the phone

Software (15%)

  –A phone App to visualize the sensor info

  –Sensor info can be stored in Google Firebase

Dancing coach on a phone (35%)

  -A classification problem based on the sensor data

    --9 movements for each leg

    --81 outputs

  -Training data: > 1K for each category

  -Grading criteria

    --Accuracy

    --Response time

B. About force sensing resistor(FSR) insole

download test code

http://thats-worth.blogspot.com/2014/07/fsr-force-sensing-resistor.html

C. About ITRI insole sensor

--Communications Protocol

--Code of packet switching

--Sensor and its corresponding signal

--Details about packet

   ---Packet size : 135 bytes

       • Insole sensor: 89 bytes

       • Datas that you don't care: 25 bytes

       • Packet information: 21 bytes

   ---"00 FE 80"  indicate the beginning of a bluetooth packet

   ---"FF" to indicate the end of  a packet

--Manual and APK for your reference

D. Project proposal 

You will need to submit a 5-page project business proposal

Due  11/02

--Project summary/abstract (作品摘要)

--Project design (產品設計:3D model)

--Business model (營運模式流程圖)

--Novelty (創新與進步性)

--Feasibility (產品可行性: tech/business)

--Niche (產品利基:與同類產品比較)

--Market value(市場或經濟價值)

--Job distribution

--References

E. Demo your project

--In the end of semester, you will demo your project in-class

--Each team has to make 5-min video to demo your project

  ---The video should be kickstarter-like for promoting your product

--The video should be uploaded to youtube in advance

--The project demo will be scored by me and also peer students 

F. What the demo should look like

https://www.kickstarter.com/projects/plxdevices/kiwi-3-obd-car-to-smartphone-interface-reinvented?ref=nav_search&result=project&term=obd

It’s expected to look like commercial-grade advertisement that can attract people

You also need to submit all the source codes and physically demo it to the TA before the in-class public demo

G. Projects in last course 

https://drive.google.com/drive/folders/1DOSCQBaY9sHBUb5sPJklZDrcauMbsPZI?usp=sharing

H. Evaluation of project 

Week 9: Midterm proposal (7%)

Week 12: Hardware (20%)

Week 14: Visualization (15%)

Week 17: in-class demo of dancing pad (28%)

 

I. Project/proposal discussion

Week 10 to week 17 -–8 weeks

Every group needs to present your progress of your proposal/project

J. Project document

Mid-term

  –5 page, 11-pt-font, double-spaced idea proposal describes/explain your project (3.5%)

  –The responsibility of each team member should be clearly stated in the proposal for the purpose of grading

Final

  –Project implementation (including source codes and demo video)(3.5%)