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Advanced Internet of Things– IoT Certification
The Internet of Things (IoT) is ushering in a new era in science and technology, which will forever change our personal as well as professional lives, our consumer habits, and the way we do business. With the fast-changing world, these latest inventions and innovations will become the norm by 2020, and we estimate more than 50 billion devices will be connected via the Internet. In order to create early adopters, we have introduced a one-of-kind course on ‘Internet of Things,’ the next big thing in the IT industry.
Why is Advanced IoT in Demand?
IoT extends computing and Internet connectivity from the most used devices like desktop and portable computers, smartphones and tablets to various variants of devices and everyday things. The data captured on these devices through sensors reveals interesting patterns with latent business values.
Businesses are increasingly interested in leveraging insights derived from data to gain value creation. This amazing technology is creating enormous opportunities for businesses to reap greater benefits by enhancing resource efficiencies and increasing productivity.
- Concept and definitions
- Embedded Systems, Computer Networks, M2M (Machine to Machine Communication), Internet of Everything (IoE), Machine Learning, Distributed Computing, Artificial Intelligence, Industrial automation
- Interoperability, Identification, localization, Communication, Software Defined Assets
- Understanding IT and OT convergence: Evolution of IIoT & Industrie 4.0
- IoT Adoption
- Market statistics, Early adopters, Roadmap
- Business opportunities: Product + Service model
- Development, deployment and monetization of applications as service
- Use cases
- Knowledge discovery process
- DIKW pyramid and relevance with IoT
- Microcontrollers: cost, performance, and power consumption
- Commercial microcontroller based development boards
- Selection criteria and tradeoffs
- Industrial networks, M2M networks
- Transducer: Sensor and Actuator
- Sensors – Types of sensors, sampling, analog to digital conversion, selection criteria of sensor and ADC
- Data acquisition, storage and analytics
- Signals and systems
- Signal processing, systems classification, sampling theorem, ensuring quality and consistency of data
- Real time analytics
- Understanding fundamental nuances between IoT and Big data
- Usage of IoT data in various business domains to gain operational efficiency
- Edge analytics
- Data Aggregation on Edge gateway
- Sensor nodes
- Sensor node architecture
- WSN/M2M communication technologies
- Bluetooth, Zigbee and WiFi communication technologies
- Cellular communication and LPWAN (LoRa and LoRaWAN) technologies
- IoT reference architectures
- Standardization initiatives
- Interoperability issues
- IoT design considerations
- Architectures Device, Network and Cloud
- Centralized vs distributed architectures
- Networks, communication technologies and protocols
- Smart asset management: Connectivity, Visibility, Analytics, Alerts
- Public, Private and Hybrid cloud platforms and deployment strategy
- Industrial Gateways
- Commercial Gateways solutions from various vendors
- Cloud based Gateway solutions
- IaaS, SaaS, PaaS models
- Cloud components and services
- Device Management, Databases, Visualization, Reporting, Notification/Alarm management, Security management, Cloud resource monitoring and management
- Example platforms: ThingSpeak, Pubnub, AWS IoT
- AWS IoT Services
- Device Registry
- Authentication And Authorization
- Device Gateway
- Rules Engine
- Device Shadow
- AWS IoT Services
- Standards and Best practices
- Common vulnerabilities
- Attack surfaces
- Hardware and Software solutions
- Open source initiatives
- Descriptive, Diagnostic, Predictive and Prescriptive
- Analytics using Python advance packages: Numpy, Scipy, Matplotlib, Pandas and Sci-kit learn
- Cold chain monitoring
- Asset tracking using RFID and GPRS/GPS
- Programming microcontrollers (Arduino, NodeMCU).
- Building HTTP and MQTT based M2M networks.
- Interfacing Analog and Digital sensors with microcontroller to learn real-time data acquisition, storage and analysis on IoT endpoints and edges.
- Interfacing SD card with microcontroller for data logging on IoT end devices using SPI protocol.
- Interfacing Real-time clock module with microcontrollers for time and date stamping using I2C protocol.
- Python exercises to check quality of acquired data.
- Developing microcontroller based applications to understand event based real time processing and in-memory computations.
- Setting up Raspberry Pi as Gateway to aggregate data from thin clients.
- Python programming on Raspberry Pi to analyze collected data.
- GPIO programming using Python and remote monitoring /control.
- Pushing collected data to cloud platforms.
- Designing sensor nodes to collect multiple parameters (Temperature, Humidity, etc).
- Uploading data on local gateway as cache.
- Uploading data on cloud platforms.
- Monitoring and controlling devices using android user apps and Bluetooth interfaces.
- Building wireless sensor networks using WiFi.
- Sensor data uploading on cloud using GSM/GPRS.
- Device to device communication using LoRa modules.
- Remote controlling machines using cloud based apps.
- Remote controlling machines using device based apps through cloud as an intermediate node.
- Interfacing Raspberry Pi with AWS IoT Gateway service to exchange messages.
- Interfacing Raspberry Pi with PUBNUB cloud to understand publish/subscribe architecture and MQTT protocol.
- Data cleaning, sub setting and visualization.
- Set of python exercises to demonstrate descriptive and predictive analytics.
- Case study/Use case:
- Environment Monitoring
- Health monitoring (Wearable)
- Asset performance monitoring
- Raspberry Pi 3
- Arduino Mega (ATMega2560) with USB cable
- ESP8266 NodeMcu
- Sensors – Analog temperature sensor(LM35)
- IR Proximity Sensor
- Switches – Push Button (10)
- LEDs (10)
- Resistors (10)
- Connecting leads (25)
- Memory Card (16 GB)
- HDMI – VGA Converter
- 1A Power Adapter
- WiFi – ESP01
- Bluetooth – HC05
The duration of the course is 48 hours which includes 18 hours of theoretical sessions and 30 hours of hands on sessions.
Internet of Things has a wide horizon for the IT professionals, electrical and electronics engineers, designers and solution architecture. It can also be a boon for the existing and budding entrepreneurs who are interested in building solutions for their customers. Professional working in other sectors like pharmaceutical, real estate, sales, finance, designing, manufacturing, electrical, retail, healthcare, etc. can also take benefit from IoT solutions. Graduates and freshers can also kick start their career with the Internet of Things.
The kit includes: Raspberry Pi 3, Arduino Mega (ATMega2560), Memory Card (16 GB), HDMI – VGA Converter, 1A Power Adapter, Sensors – Analog temperature sensor(LM35), IR Proximity Sensor, Switches – Push Button (10), Breadboard, LEDs (10), Resistors (10), Connecting leads (25), WiFi – ESP8266 ESP01/ESP12E (breakout Board) and Bluetooth – HC05 will help you to perform all the practical’s with snapshots. The hardware components will be shipped by us to your home.
Yes, all our sessions are recorded. Therefore, if you ever miss a class, you will be able to view it on our LMS.
The course material is accessible for lifetime post-training.
After you successfully complete the training program, you will be evaluated on few parameters – Attendance in sessions, Objective examination and others. Then you will be certified by Collabera TACT.