Post Graduate Programme in Internet of Things Everything about the Internet of Things

Transcription

1 Post Graduate Programme in Internet of Things Everything about the Internet of Things

2 Index Programme Highlights...4 Programme Objective...5 Learning Outcomes...5 Courses in the Programme...6 Who Should Apply...6 Eligibility...6 Programme Fee...7 Application Instructions...7 Meet the Instructors...8 Programme Curriculum a. Course 1: IoT Technology & Applications...9 b. Course 2: Communication & Networking Technologies in IoT...11 c. Course 3: Hardware Architectures for IoT...13 d. Course 4: Sensors, Actuators, & Signal Processing...15 e. Course 5: Software & Programming in IoT...17 f. Course 6: Data Management in IoT...19 g. Course 7: Capstone Project...22 FAQs

3 Post Graduate Programme in Internet of Things Join the exciting world of connected devices through an innovative programme on Internet of Things. Learn about the building blocks of IoT and gain insights into the design & development of IoT Applications. Today, technology drives an ever-increasing number of things around us. Fitness trackers, smart homes and gaming devices are seamlessly connected with our lives, enabling us to enjoy a greater degree of personalized and immersive experience. At the same time, commercial applications such as industrial automation, remote surgery and drones are helping corporations achieve unprecedented scale of operations. This is the world of IoT. The 10-month Post Graduate Programme in Internet of Things is an advanced-level programme from BITS Pilani that uses a blend of lectures and experiential learning tools to provide expertise in ideation, design, development, and deployment of IoT applications and systems. This interdisciplinary programme helps the learner gain expertise in the four building blocks of IoT - hardware, software, applications systems and data. 03

4 Programme Highlights 10-month comprehensive Post Graduate programme covering software, hardware, application systems, big data, and their interplay in IoT systems A 6-week Capstone project where you will design, build and implement a prototype IoT system, under the mentorship of BITS Pilani instructors Extensive digital content including expert lecture videos, and engaging digital learning material A 2-day Campus Immersion module during which participants will visit the Goa Campus of BITS during the programme Accessibility to BITS Pilani instructors through a online live lectures, a responsive Q&A support and discussion forums Participants who successfully complete the programme will become members of an elite & global community of BITS Pilani Alumni Hands-on experiential learning through remote labs that provide access to leading IoT platforms such as ARM Cortex based STM32, Raspberry Pi & Arduino Participants who successfully complete the programme will receive a Post Graduate Certificate in Internet of Things. Such participants can apply to M.Tech. Embedded Systems offered by BITS Pilani Work Integrated Learning Programmes * The Post Graduate Certificate in Internet of Things will allows learners to earn Academic Credits which can be transferred to the M.Tech. Embedded Systems programme offered by BITS Pilani Work Integrated Learning Programmes. The credentials will count towards one semester of the four-semester M.Tech. Embedded Systems programme. For admission to M.Tech. Embedded Systems, applicants must meet eligibility requirements as mentioned on the BITS Pilani website. 04

5 Programme Objective This programme aims to enable the learners to gain expertise in key areas of IoT such as end device development, Cloud Computing, Network Design & Management, Application Interface Design & UI, and Distributed & Big Data Management. Learning Outcomes 1 Understand the building blocks of IoT technology and explore the vast spectrum of IoT applications 4 Connect the cyber world with the physical world of humans, automobiles and factories 2 3 Use processors & peripherals to design & build IoT hardware Assess, select and customize technologies for IoT applications 5 6 Integrate geographically distributed devices with diverse capabilities Design and implement IoT applications that manage big data 05

6 Courses IoT Technology & Applications 6 weeks Communication and Networking Technologies in IoT 6 weeks Hardware Architectures for IoT 6 weeks Software and Programming in IoT 8 weeks Data Management in IoT 3 weeks Capstone Project 6 weeks Sensors, Actuators, and Signal Processing 6 weeks Who should Apply? Eligibility The programme is designed for engineers who wish to transition to IoT career opportunities in sectors such as IT, Automotive, Manufacturing, Energy, Telecom and Logistics. Engineers currently working in organisations that either provide IoT products & services, or design & implement IoT solutions for transforming their own business should also consider applying to this programme. Working professionals holding BE/ B.Tech. or equivalent in Comp. Sci./ Info. Sys./ Electronics/ Electrical/ Instrumentation or related domains. 06

7 Programme Fee INR 2,25,000 (including GST) Fee Payment Schedule Block amount (within 7 days of reciept of provisional Admission Offer Letter) INR 25,000 Installment 1 (within 15 days of reciept of Final Admission Offer Letter) INR 1,00,000 Installment 2 (before July 15, 2018) INR 1,00,000 Programme Begins Jan 12, 2018 Application Instructions 1. Click here to register yourself on the Online Application Center. Log in to fill up and submit the completed Application Form. 2. You will receive a Provisional Admission Offer Letter within 2 days of receipt of your Application Form. 3. Upon receiving the Provisional Admission Offer Letter, you will need to submit the following within 7 days using the Online Application Center: a. Block amount of: INR 25,000 b. Scanned copy of Passport size photograph c. Scanned copy of self attested Graduation degree certificate and marksheets d. Proof of ID (Govt. issued ID such as Driving License, Passport, Aadhar, Voter ID, etc.) e. Proof of employment, such as Work Experience Certification from current employer. 4. Within 7 days of receiving the block amount and other supporting documents, you will receive a Final Admission Offer Letter. You will need to submit the First Installment (INR 1,00,000) within 15 days of receipt of this letter. 5. Upon receipt of the remaining First Installment, you will recceive your BITS Student ID, detailed programme schedule and access to the learning platform. 6. Second Installment (INR 1,00,000) is payable before July 15th,

8 Meet the Instructors Prof. KR Anupama Prof. Haribabu Prof. Chandra Shekar RK Prof. Brajabandhu Mishra Prof. K G Krishna Prof. Anita Ramachandran Prof. Vinay Chamola Prof. G.S Sesha Chalapathi Prof. Meetha V Shenoy Prof. Sreejith V 08

9 Course 1 IoT Technology & Applications Develop an understanding of IoT technology and Cyber-Physical Systems. Explore the vast spectrum of IoT applications and gain an appreciation of the building blocks of IoT. Internet of Things is gaining widespread adoption across users and industries. With an estimated 25bn IoT-based things by 2020, hardware and software engineers will find it absolutely necessary to have at least an appreciation of the fundamentals behind this technology. This six-week course provides an overview of IoT applications and their life cycles. Using case analysis and assignments, learners will acquire skills necessary to identify building blocks and design issues of each application. The course also offers an introduction to IoT platforms, end devices, networks and cloud services. Learning Methodology The course makes use of experiential learning components such as Case studies, and Practical demonstrations of two IoT applications Smart Lighting System and Weather Monitoring System using Raspberry Pi platform. Learning Outcomes Upon successful completion of this course, learners will be able to: 1. Identify issues and design challenges in IoT applications 2. Select appropriate hardware and software components for IoT applications 3. Lay out the design / life cycle for IoT applications 09

10 Curriculum: IoT Technology & Applications Module IoT Introduction Design Methodology & Life Cycle IoT Platforms & End Devices IoT Network & Cloud Services IoT System Design Examples IoT Applications Topics a. Introduction to IoT & Cyber-Physical Systems b. IoT Enabling Technologies Physical End points, Network Services, Cloud c. Different Levels of IoT Applications Level 1-6 with examples a. Design Methodology IoT Reference Model A i. Example Level 1 System Smart Lighting b. Design Methodology IoT Reference Model A ii. Example Level 6 System Weather Monitoring a. Introduction to IoT Physical End Points & Platforms b. Raspberry Architecture c. Raspberry OS & Programming d. Raspberry PI I/O Interfaces e. Raspberry Communication Interfaces a. Introduction to IoT Network & Cloud Services b. Link, Networking, Transport and Application Layer Protocols c. IoT Communication APIs- REST & Web Socket d. Introduction to Cloud Service Model a. Smart Lighting System Hardware & Software Design, Implementation with Demo b. Weather Monitoring System Hardware & Software Design, Implementation with Demo a. Healthcare - Applications Overview Enabling Technologies Challenges in Design & Development b. Health Care Example Fitness Tracking Systems Key Design Challenges Generic Fitness Tracking System Architecture Building Blocks- Processor Building Blocks - Sensors Building Blocks -Cloud & Communication Building Blocks - OS c. Transportation and Logistics - Applications Overview Enabling Technologies Challenges in Design & Development d. Smart Environments - Industrial application (Process control), Home automation Overview Enabling Technologies Challenges in Design & Development e. Smart Home Example Introduction Generic Architecture 10

11 Course 2 Communication and Networking Technologies in IoT Learn to assess, select and customize communication and networking technologies for IoT applications across a broad spectrum of domains. IoT applications require data generated or acquired across geographically dispersed components to be processed collaboratively. This is achieved using appropriate communication systems and networks. This six-week course provides an overview of various network models and technologies used in IoT systems. The learner gains insights into the characteristics of the complementary and competing technologies, analyses vulnerabilities and design network solutions. Learning Methodology This course uses experiential learning components such as: 1. Simulation-based assignments on NS2 for design and analysis of network models 2. Laboratory exercises with NS2 Learning Outcomes Upon successful completion of this course, learners will be able to: 1. Compare and assess different network models and techniques in IoT systems 2. Use relevant communication protocols to design and deploy applications in different industries such as manufacturing and automotive 3. Identify security vulnerabilities in wireless networks, IoT applications and devices, and outline solutionsv 11

12 Curriculum: Communication and Networking Technologies in IoT Module Introduction to Networking Network Models & Architecture Common Network Standards Network Security & Privacy Topics a Introduction Application 1 Fitness Tracking System Application Overview Network Requirements Network Hierarchy b Introduction Application 1 Fitness Tracking System Application Overview Network Requirements Network Hierarchy c Communication & Networking Requirements in IoT d TCP/ IP Stack e Wired & Wireless Networks a. Communication Models Client-Server Publisher Subscriber P2P b. Introduction to NS2 c. Ad Hoc WSN MANET VANET d. Interfacing to Structured networks Broadband, Cellular, Satellite a & variants b. Bluetooth & variants c & variants d. Other Standards NFC LORA DSRC, WAVE e. Industrial & Automotive Networks f. Industrial networks g. Vehicular networks (CAN, Modbus, Ethernet/Industrial Protocol, MQTT, TTP/C, Flexray) h. Summary (Case studies) a. Issues & Challenges Security attacks Security solutions 12

13 Course 3 Hardware Architectures for IoT Develop an understanding and use of typical processors & peripherals relevant to IoT, and design & build IoT hardware. IoT systems are built on top of a network of components of varying complexity and computing capabilities, ranging from RFID tags, smart sensors and smartphones to multi-core embedded computers. It is important for hardware and software engineers to be able to architect custom hardware for IoT systems. This six-week course delves deep into the internal architecture of these individual components within the IoT system. The learner will understand the characteristics and limitations of components such as processing units, memory, buses and associated peripherals in the context of IoT applications. This will enable the learner to analyses processing requirements of applications, design sub-modules to meet these requirements and architect the hardware using them. The analyses involved includes power consumption, timing and performance. Upon completion, the learner should be able to design these components. Learning Methodology The course makes use of experiential learning components such as Case studies, and Practical demonstrations of two IoT applications Smart Lighting System and Weather Monitoring System using Raspberry Pi platform : 1. Case demo of an IoT end device 2. Lab exercise on STM32 3. System design assignments focusing on hardware design lifecycle using STM32 4. Case demo of application on specific processor Learning Outcomes Upon successful completion of this course, learners will be able to: 1. Understand processor architecture relevant to IoT applications 2. Build IoT hardware using components - processors, memory and peripherals 3. Measure and optimize performance of IoT hardware 4. Optimize speed vs. power in IoT applications 5. Leverage on-board/ on-chip buses and I/O interfaces 13

14 Curriculum: Hardware Architectures for IoT Module Microprocessors & Microcontrollers for IoT IoT Platforms Memory Clock, Timing, Interrupt Buses I/O Power Consumption and Management Summary: Topics a. ISA & Micro-architecture Introduction RISC/ CISC Parallel Architectures (ILP, DLP,TLP) a. Introduction to IoT applications b. IoT Platforms c. ARM architecture Scalar d. ARM architecture Superscalar a. Memory Hierarchy, Types Memory Access Models Memory Management Unit Memory Protection b. Cache Cache Hierarchy Cache Architectures Cache Consistency and Coherence Models a. Clocking & Clock gating b. Timers Platform specific and non-specific a. Interrupts b. Interrupt latency, jitter c. Priority Logic d. Interrupt handlers a On-chip buses System Bus -AMBA Peripheral bus USB, SPI, I2C, UART, Microwire a. I/O Devices Ports Storage devices ISP/IAP b. Modes of Transfer Polling Interrupts DMA a. Energy Consumption Analysis b. Power Management Static Techniques Dynamic Techniques Low power modes System design example 14

15 Course 4 Sensors, Actuators, and Signal Processing Learn how to connect the cyber world (computers and internet) with the physical world (e.g. human body, automobiles, factories). IoT systems are made up of a large number of components that sense data or control events. Building IoT systems requires interfacing sensors and actuators with computing devices and networks. Often the raw sensor data has to be digitized and processed. This six-week course provides an understanding of technologies and interfacing requirements for sensors and actuators of varying complexity. The learner will obtain knowledge of signal processing techniques and interfacing techniques. Algorithms and techniques for fusing data from multiple sensors as well as for compressing data will also be covered. Learning Methodology This course uses experiential learning components, including sessions on Interfacing Sensors & Actuators to IoT platforms, and Data fusion & processing on IoT platforms Learning Outcomes Upon successful completion of this course, learners will be able to: 1. Categorize sensors based on complexity 2. Interface Smart Sensors to the Internet 3. Control actuators via the Internet 4. Interface multimedia data acquisition devices / sensors with computing devices 5. Use HCI/ BCI in IoT applications 15

16 Curriculum: Sensors, Actuators, and Signal Processing Module Sensors Raw Sensor Data Acquisition Multi-Sensor Fusion Advanced Sensing Techniques Actuators and Controllers Topics a. Categorization based on complexity b. Introduction with applications c. IR/Ultrasonic proximity & distance measurement, Accelerometers, Gyroscope, magnetometer d. Biometric Sensors Heart rate, ECG e. Image/Photo Sensors f. Acoustic Sensors 1. Sampling, Synchronization 2. Signal Processing and Conditioning 3. Interface of Sensor to internet a. Algorithms & Techniques b. Data Compression/Decompression c. Case studies a. BCI b. HCI c. Other advanced techniques a. Categorization based on complexity a. Industrial Controllers Standards & Protocols a. Actuators Motion control, motor control, relays, solenoid valve, IP based control a. Control of Actuators via Internet, Cloud based control. Case Study 16

17 Course 5 Software and Programming in IoT Learn how to orchestrate the communication and collaboration between a large numbers of geographically distributed devices with diverse capabilities. Software life-cycle of an IoT application differs significantly from that of conventional software. This eight week course covers lifecycle of application software by focusing on IoT context at each stage: 1. requirements (connectivity, constraint and scale of devices) 2. architecture (hardware, software and communication) 3. design (client-server software) 4. deployment (distributed and constrained devices) The learner will understand: 1. The impact of running an application on constrained devices 2. Design and implement a client software on smart devices 3. Design & implement RESTful services and deploy it on cloud Learning Methodology This course uses experiential learning components, including sessions on: 1. Android Programming involving user interface, SQLite database, Actions, and Intents 2. Developing applications on Raspberry Pi and Arduino 3. Server-side development of RESTful service using SOAP/CoAP. 4. Programming using Embedded Linux Learning Outcomes Upon successful completion of this course, learners will be able to: 1. Architect IoT application software 2. Analyze the impact of OS and runtime environment on an IoT application (in terms of memory access, concurrency, communication, and scheduling) 3. Design and implement IoT client software on mobile devices including user interface, database access, event handling and communication 4. Design server-side/ cloud-end of the IoT application 5. Understand commonly used tools and technologies for IoT application development 17

18 Curriculum: Software and Programming in IoT Module Topics IoT Software Architectures Life cycle model Modular Architectures Introduction to operating system Android Client development a. Components of Operating systems Process, Thread Concurrency Memory Model I/O Communication b. Task priority and Criticality Real time scheduling algorithms c. Inter-process Communication & shared memory Locks Shared memory Remote procedure calls 1. Android Application Architecture 2. UI Components Layouts Views Buttons 3. Activities & Intents Activities Intents 4. Connectivity Communication over Bluetooth Communication over Internet 5. Device database Working with SQLite database Server-side Application Development Developing Applications on Raspberry Pi Overview of commonly used software development technologies in IoT 1. Web-server implementation & deployment Web-server implementation & deployment Implementing RESTful services (SOAP/CoAP) 1. Developing Applications on Raspberry Pi Set up Raspberry Pi Sensor based IoT Application development on Raspberry Pi 1. Commonly used software development technologies & languages in IoT Commonly used tools Commonly used OS 18

19 Course 6 Data Management in IoT Learn how to design and implement IoT applications that manage big data, streaming data, and/or distributed data. The learner will be able to programme IoT applications to manage data where data volume and/or data rate is high or data is streamed. The course covers techniques to identify end-to-end data flow characteristics of an application and apply appropriate messaging models to build solutions. This three week course covers techniques for large scale processing of data on the server / cloud including analytics using tools. The course covers algorithms / techniques for specific patterns for distributed processing on the devices as well as techniques for fault-tolerant data processing. Learning Methodology The course makes use of experiential learning components such as Case studies, and Practical demonstrations of two IoT applications Smart Lighting System and Weather Monitoring System using Raspberry Pi platform : 1. Lab exercises / programming assignments on : a. TinyDB for Data Acquisition in Sensor Networks b. Hadoop and Apache Storm for Big Data 2. Project and Case study involving end-to-end data flow, fault-tolerant distributed processing in large scale network of devices/ clients, backend processing of big data. Learning Outcomes Upon successful completion of this course, learners will be able to: 1. Manage data in IoT systems 2. Perform Data acquisition in Sensor Networks 3. Perform Data acquisition in RFID 4. Manage Big Data in IoT systems 19

20 Curriculum: Data Management in IoT Module Topics Data in IoT What is data management? Data life cycle in IoT with a usecase; Data sources in IoT Multipurpose computers, Specialized embedded devices, Connected Sensors, passively trackable objects with examples Data centric IoT products Context-action frame work, Smart Systems, Ambient Analytics, Personal Assistants, Quantified Self Flow of Data in IoT On-device processing vs Edge (fog) computing vs Cloud processing Types of IoT Data: Information about the physical world; Information about things itself (location or state); biometrics; human behavioral data Static vs dynamic data, Direct vs inferred data, Big vs small data, Real-time vs historical data, Timing and frequency of data collection Challenges in managing IoT data-1 IoT Architectures: Dedicated gateway; Smartphone as gateway; Direct internet connection; Device-to-device connections; Service-to-service connections; Networking issues: IoT devices connect to network intermittently; latency responsiveness; reliability; Examples; Challenges in managing IoT data-2 Energy Constraints; Volume; variety; velocity Data Acquisition in Sensor Networks Characteristics of WSNs Processing, network and storage capabilities of sensor motes; Use cases; Characteristics of sensor data; Challenges in using traditional database systems; Data models for WSNs Relational data model; Data streams; Handling data streams in relational data model; Timestamp ordering; Query languages Query processing in WSN Relational operators applied to WSN; Aggregation operators in WSN; Issues in Data stream query processing- continuous queries, blocking operators; Sliding windows; Query optimization issues Heuristics; query processing cost in WSN; Examples; Data Acquisition approaches Comparison of Cougar; Fjord; TAG; TinyDB TinyDB-1 Data model; basic language features; Event based queries; Other queries defined in TinyDB; TinyDB-2 Power-based query optimization; Semantic Routing Trees; Data Aggregation; Sensor Data Cleaning-1 Sources of errors in sensor data: systematic bias, random noise; Online Bayesian approach 20

21 Module Topics Sensor Data Cleaning-2 Other approaches; Sensor Data Storage Distributed vs Centralized data storage models; Geographic hash table (GHT); Multi-tier storage architecture (TSAR); SQUIRREL; Data Acquisition in RFID Characteristics of RFID data Stream of tuples; Huge volume; Inaccuracy; Spatial and temporal aspects; RFID Data Cleaning-1 Missed data readings and Unreliable readings: Temporal granules and spatial granules; RFID Data Cleaning-2 Sliding window estimation (SMURF); RFID Data Cleaning-3 Data redundancy-redundancy at reader level, redundancy at data level; RFID Data Preparation Inference Rule Materialization; Lineage tracing in RFID Overview Traditional data processing vs stream processing; Basic streaming methods: computing mean and standard deviation; Time Windows; Event processing Events; Complex Events; Complex Event processing; Event Processing in RFID SASE language for RFID; Mining Data Streams-1 Challenges: Data uncertainty, volume, power constraints, in-network processing; Mining Data Streams-2 Data Stream clustering; Mining Data Streams-3 Data classification; Frequent pattern mining; Mining Data Streams-3 Change detection in data streams; Synopsis construction; Dimensionality reduction; Forecasting; Case study: health care systems-1 Mining sensor data in Medical informatics: scope and challenges; Case study: health care systems-2 Sensor data mining applications Bigdata management in IoT Bigdata storage Relational vs no-sql databases; CAP theorem; Examples of Cloud services; Bigdata processing-1 Using Hadoop MapReduce for Batch data Analysis Bigdata processing-2 Using Apache Storm for real-time data stream analysis 21

22 Course 7 IoT: Capstone Project Demonstrate your knowledge and skills acquired in the Post Graduate Programme in Internet of Things by Designing and Implementing an end-to-end IoT system involving Hardware, Software and Networking elements In this six week Capstone project, you will be able to design, build and implement a prototype IoT system which encapsulates analysis of environments amenable for IoT implementation by arriving at project goals, various design choices and trade-offs you would make in arriving at practical solutions to real-world problems. During the course of this project, you will have a chance to revisit some topics and reflect on the learnings from previous course modules while you adapt them for your application. Project Methodology Under the guidance of BITS Pilani faculty members, you will follow a six-week structured project plan to: 1. Review key concepts from past IoT courses 2. Select a project area and adopt a formal development methodology 3. Begin building a prototype IoT system, making design choices along the way 4. Present the working prototype to the instructors and submit a technical report 5. Receive and reflect upon active feedback from instructors through each stage You will have full freedom to be creative and think through the problem and its solution--we will be guiding you along the way via discussion forums illustrating the underlying concepts, development methodology and demonstrations of building one such example project prototype. Whatever project you identify, we expect you to be involved in Full-stack implementation (Sense Compute Respond), from wiring-up physical hardware (sensors, boards) and connecting to Cloud IoT platform to writing Smart user-friendly application programs that source data streams, analyze, and predict behavior or perform intelligent action. Though the working prototype you build during this Capstone project is not expected to be a fully-functional and field-deployable system, you are asked to adopt appropriate choice of formal methodologies (like Agile or Iterative/Incremental models) and produce deliverables such as Project Charter, Requirements Document, System Architecture, Design Specification, System Test Cases, User Acceptance Criteria, and Deployment Model, etc in addition to the final working prototype. Your final presentation for evaluation can be in the form of short video presentation (recorded) showcasing your project and your technical communication skills along with the above reports and conclusion 22

23 Learning Outcomes The Capstone project will help you develop critical skills to further your career in the exciting field of Internet of Things. You will be able to: 1. Identify opportunities for enabling Smart environments using IoT technologies 2. Design and Implement end-to-end IoT Solutions by analyzing various technology choices, design trade-offs and implementation issues 3. Learn formal system development methodology and hone your technical communication skills Environment for IoT Smart City Home Automation Smart Agriculture Representative Project Areas (not limited to ) Energy Management, Water-supply and Sanitation, Traffic Management Energy-efficient Buildings, Elderly care, Smart Home with Smart Appliances Sustainable farming, Precision Agriculture, Water management, Agribots Industry 4.0 egovernance Transportation & Logistics Healthcare Digital Manufacturing, Offshore oil and gas platforms, Personalized Insurance Citizen-friendly Services, Real-time Monitoring, Regulation & Law enforcement Autonomous vehicles, Fleet Management, Railway Track Signalling systems Telemedicine, Body Area Networks, Telesurgery (Cyber-physical systems) Curriculum: IoT: Capstone Project Module Topics IoT--An Architectural Overview; Industry Standards and APIs; Selecting the Right sub-system/component Requirements Engineering; Modeling and Architecture; Hardware and Software Tools for Prototyping Instrumenting the System and Interfacing to IoT Cloud Platforms: Identifying Sensors/Actuators and Networking of Sensor-nodes/Controllers; Hardware interfacing and programming of an actual implementation; Identifying scope for Edge-computing; Interfacing and programming the Cloud Services Programming for the Analytics: Writing optimization/analytics programs (in Python/Java) by accessing Machine Learning libraries provided by the IoT platform Analytics Reports/Actuation of devices: Demonstrate how the intelligence acquired from processing of sensor data is looped back in real-time to the devices in the environment Walking through the entire IoT system implemented in the above modules; Highlight the role of OS, IoT Platform and the Programming Environment in building scalable IoT systems; Practical tips for successful implementation; Preparing Feasibility Reports for IoT projects; and summarization of Learning Experience in the Capstone Project 23

24 FAQs 1. Who is this programmeme designed for? The programme can be pursued by Engineers who hold B.E or B. Tech in Computer Science, Electrical, Electronics, Instrumentation or related fields. This is ideally suited for two types of engineering professionals: a. Technology Professionals in the IT industry who wish to transition into, or join roles that involve designing and developing IoT Solutions. b. Professionals who are working in sectors such as Automotive, Manufacturing, Telecom, Energy and Logistics etc. where they aspire to be involved in deploying IoT solution in their organization. So, if a professional has the required qualifications and a desire to accelerate his or her career in the rapidly growing IoT industry, this is the ideal programme. 2. What certification do I receive at the end of the programme? Upon successful completion of the programme, participants will receive a Post Graduate Certificate in Internet of Things from BITS Pilani in addition to an Official Transcript and Programme GPA. 3. Will I become an alumni of BITS Pilani upon completion of this programme? Yes. The qualification will provide you the prestigious BITS Pilani Alumni status, through which you will become member of an elite & global community of BITS Pilani Alumni. 4. How is this programme different from others? a. It is a unique interdisciplinary programme that covers all key aspects of IoT including hardware, software, application systems and data. b. BITS Pilani has set up a dedicated IoT lab which can be accessed by busy working professionals remotely. The lab has leading IoT platforms such as ARM cortex based STM32, Raspberry Pi & Arduino which you can control and operate the equipment from your own location using the internet and run experiments on high end equipment. c A rich & flexible learning methodology allows one to pursue the programme without any career break. Engaging digital learning experience that involves expert lecture videos, assignments, online live classes and discussion forums. In addition you will also be able to clear your doubts through periodic live sessions with faculty and active online discussion forums. d. The programme includes a 6-week rigorous project under the guidance of BITS Pilani faculty members to create a working prototype of an exciting IoT product in areas such as Smart city, Home automation, Digital manufacturing, Telemedicine and Agribots. e. The programme includes a 2-day campus immersion at the Goa Campus of BITS Pilani. All participants will need to travel to Goa over a 2-day weekend and participate in a special faculty interaction and engaging learning activities. As a BITS Pilani participant, you would be expected to stay at the Campus hostel for an immersive academic experience. f. Successful completion of the programme will provide you the prestigious BITS Pilani Alumni status, through which you will become member of an elite & global community of BITS Pilani Alumni. 5. What is the weekly time commitment expected? Participants will be expected to devote 8-10 hours each week to fully benefit from programme. You will be able to engage with lecture videos, complete periodic assignments, and interact with the cohort through discussions forums for a rich academic experience. 24

25 6. How will my doubts/questions be resolved in an online programme? Programme participants will be able to engage with instructors to clear their academic doubts: a. Periodic live sessions with instructors will help you to clear your doubts and seek answers. b. BITS Pilani faculty members and Teaching Assistants will be available through discussion forums and . c. Discussion forums will help you interact with other participants to seek an offer support. 7. What is the Capstone Project? The programme includes a 6 week rigorous project to create a working prototype of an exciting IoT-related areas such as Smart city, Home automation, Digital manufacturing, Telemedicine and Agribots. Throughout the project you will work under the mentorship of BITS Pilani faculty to design, build and implement a working prototype IoT system. Your project work is the showcase to the industry of your expertise in IoT. 8. Is there any minimum qualification required to apply for this programme? The programme can be pursued by Engineers who hold BE/ B.Tech. or equivalent in Computer Science, Electrical, Electronics, Instrumentation or related domains 9. Will I get a job after this programme? IoT industry is growing faster than the IT industry. This certainly means that skilled professionals will be in high-demand in this area. BITS Pilani has studied the skills required for popular IoT roles such as IoT Platform Developer, IoT Solution Architect, Data Manager for Smart Devices, and many other rewarding opportunities. The curriculum has been mapped to these roles and provides you with the knowledge, skills and expertise required to take up these in any IoT project or organization. We believe that armed with these skills an engineer will be sought after by the industry. Please note that BITS Pilani does not offer placement assistance as a part of this programme. 10. What is the Refund/ Deferral guidelines in case I am unable to continue, or need to take a break between the programme? Refund: Participants may cancel their admission upto the first 7 days from the start of the cohort i.e. Programme Start date (launch of Course 1). He/ She will be eligible to get a full refund of his programme fee paid, minus the bank processing charges and applicable taxes (the taxes won t be refunded). Refund will be processed within a maximum of 45 working days. The participant will be required to fill in a refund form that will be made available by the Admission Cell. Deferral: If a participant is facing severe issues in dedicating time to the course, we provide the opportunity for the participant defer to another batch. Participants can request for deferral ONLY ONCE and to the next immediate scheduled cohort of the same programme. Participants will be required to pay a deferral fees of 10% of programme fees (including GST). The deferral request will be approved once the deferral fees is paid. Till this is completed, the participant will be assumed to be continuing in the same cohort. Participant will start learning on the new cohort from the point of leaving the deferred cohort. If, however, the deferral request is raised before the issue of BITS Student ID, the 10% deferral fees will not be charged and participant will be deferred to the next scheduled cohort. However, in case there is any fee differential between his current cohort and the cohort he/she has deferred to, the participant will have to pay the differential amount. 25

26 Work Integrated Learning Programmes