Internet Of Things
Engineering Innovations and Commercialization
Internet of Things - Engineering Innovations and Commercialization
Columbia University course EECS E6766
Zoran Kostic, Professor of Professional Practice, zk2172(at)columbia.edu
Electrical Engineering Department, Data Sciences Institute, Columbia University in the City of New York
Open to students with both engineering and non-engineering backgrounds (such as business).
Course in a nutshell:
Training students in rigorous engineering and entrepreneurial approach to innovation and product development using the example of Internet of Things. Case-study based. Mixed-expertise student teams work on projects whose output is both an engineering deliverable as well as an engineering product business plan. Focus on a selected field within the scope of Internet of Things, with coverage of physical, networking and data analysis aspects. Semester-long student engagement with industry (engineers, startups founders, corporate executives, IoT analysts) through invited speakers, project guidance, and mentoring.
Bulletin Description:
Deep dive into a couple of selected topics / use-cases from the area of Internet of Things. Coverage of the topic from device to the cloud, with focus on practical aspects. Innovative product definition, product development, marketing, commercialization and monetization. Cross-disciplinary coverage: EE, MechE, CS, BioEngineering, marketing, business, design. Building products and startups in the IoT domain. Collaboration between the engineering school, business school, industry experts and engagement in IoT activities in NYC. Collaborative project by groups of students from different disciplines.
Content
Combining training in rigorous engineering and entrepreneurial domains. Case-study based. Mixed-expertise student teams work on projects whose output is both an engineering deliverable as well as an engineering product business plan. Focus on a selected field within the scope of Internet of Things, with coverage of physical, networking and data analysis aspects.
Details to be added.
Project Areas:
TBD for summer 2016
Smart Home
Smart Buildings
Smart Cities
Smart Infrastructure
Mobility and Transport
Energy
Smart Grid
Healthcare
Wearables
Data Analytics
Sensor Technologies
Security
Course open to students with both engineering and non-engineering backgrounds.
Summer 2016: May 26–July 21; full semester course in 9 weeks, 1 day a week. Section 1 for engineering students, section 2 for non-engineering students, with appropriately defined deliverables depending on the background. For Summer 2016, the course is co-presented by Adjunct Assistant Prof. Michael Wang and Assoc. Prof. Zoran kostic
This course E6766 is complementary to the course E6765 (Internet of Things - Systems and Physical Data Analytics)
Prerequisites for section 1- suggested for engineering students: Knowledge of programming; Wireless Communications (ELEN E4703) or related; or Computer Networks (CSEE W4119) or equivalent; or instructor's permission.
Prerequisites for section 2 - Instructor's permission business, marketing, entrepreneurial background.
Organization
Lectures:
Presentation of instructional material on engineering and entrepreneurial topics
Case Studies
Preexisting examples from high tech industry
Products, teams, marketing, financing
Student-led projects
Mixed-expertise teams: engineers and business/entrepreneurship
Deliverables: Engineering and business
Reports and presentations to Columbia and NYC community
Industry/business participation:
Project definition and sponsoring
Weekly presentations
Interaction with students through mentoring
Books, Tools and Resources
BOOKS:
Notes
Projects platform:
Selection of the industrial-grade HW development platforms (possibilities are Intel, Broadcom, Nordic, Raspberry Pi, others)
Amazon AWS cloud tools
Intel Edison Platform
Raspberry PI
Facebook Parse
Operating system of choice
Code development on github, bitbucket
Course sponsored by the equipment and financial contributions of:
Atmel, Broadcom (Wiced platform), Intel (Edison IoT platform), Silicon Labs (IoT platform), Amazon AWS, IBM Bluemix.