21 Tech Days - IoT and Machine Automation Contd ....(Day 2)

Continuing with the 21Tech Days, Day 2 Covers the components of IoT and Machine Automation.

IoT and Machine Automation is broadly classified into Device Management and Edge related which sensors and actuators that interface with edge/machines/devices. The edge analytics on the gateways closer to the devices will perform the storage, data cleaning and filters and finally data aggregation. IoT and Machine automation components include

 a. Smart Devices or Sensors/Device Management - Smart sensors/Devices are a part of the Data Connectivity Layer, who are continuously collecting data from the environment and transmit the information to the next layer. Some of th common sensors include – Temperature Sensor, Humidity Sensor, RFID Tags,Luminous Sensors, Proximity Sensors and more.

b. Connectivity/Communication Management – So how are the sensors connected? Most of the modern smart devices and sensors can be connected to low power wireless networks like Wi-Fi, ZigBee, Bluetooth, Z-wave, LoRAWAN etc… Each of these wireless technologies has its own pros and cons in terms of power, data transfer rate and overall efficiency. Latest protocols like 6LoWPAN- IPv6 over Low Power Wireless Personal Area Networks have been adapted by many companies to implement energy efficient data transmission for IoT networks.

 c. Gateways/Edge computing - IoT Gateway manages the bidirectional data traffic between different networks and protocols. Another function of gateway is to translate different network protocols and make sure interoperability of the connected devices and sensors. Gateways can be configured to perform preprocessing of the collected data from thousands of sensors locally before transmitting it to the next stage. In some scenarios, it would be necessary due to compatibility of TCP/IP protocol. IoT gateway offers certain level of security for the network and transmitted data with higher order encryption techniques.

 d.Standards and protocols -Standard protocols are not defined in IoT space as of today . Protocols integration seamlessly to all the connected devices is an important component to be looked upon when working with IoT platforms

e. Cloud Computing - Internet of things creates massive data from devices, applications and users which has to be managed in an efficient way. IoT cloud offers tools to collect, process, manage and store huge amount of data in real time. AWS, Azure and Google Cloud Platform is mostly the preferred cloud platform for IoT infrastructure set up.

 f. Analytics/Intelligence - Analytics is the process of converting analog data from billions of smart devices and sensors into useful insights which can be interpreted and used for detailed analysis.

 g. Monitoring Dashboard - User interfaces are the visible, tangible part of the IoT system which can be accessible by users. Most IoT pilots demand either a Web or a Mobile front End for easy visualization and monitoring of data transactions among various devices in real time.

All of the above, make up for a holistic tech components necessary to establish an IoT stack components.

By 2020 there will be 50 billion connected devices and data generated could exceed to few hundred zettabytes per year Considering all the circumstances , we need a scalable, efficient and real time way to analyze huge amount of data and also data analytics solution . In the last decade big data technologies batch and real time have improved the data storage, processing and also scalable computational capabilities. Big data and Anlaytics engine is all about collecting , storing and analyze large amount of data sets in order to discover the missing data and provide value information in quick time.

 Machine automation key applications

 Diagnostic: Understanding the cause of a faulty, prevention or issue

Maintenance: Monitoring and Predicting and adjusting maintenance intervals to optimize scheduling

Efficiency: Improving the performance of the production or the utilization of resources

Prognostic: Providing insight to avoid faults or to maintain efficiency

Optimization: Optimizing resource consumption or compliance with local government regulation

In the subsequent days, I will dwell in detail some of the use cases converging layers of IoT and Machine automation involving the components, tech stack and discuss more on specific solutions for a gamut of industries/verticals adopting digital transformation.

 #IoT #IIOT #Automation #Cloud