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Internet of Things (IoT) generate a huge amount of data or big data. Managing the flow and storage of this data is a tedious task for enterprises. Cloud computing with its different models and implementation platforms help companies to manage and analyze this data, enhancing the overall efficiency and working of IoT system. DLM, AEP, and Digital Twins are some of the solutions better leveraged through cloud platforms like Amazon Web Services (AWS) and Microsoft Azure. Read on to learn more.
Cloud computing allows companies to store and manage data over cloud platforms, providing scalability in the delivery of applications and software as a service. Cloud computing also allows data transfer and storage through the internet or with a direct link that enables uninterrupted data transfer between devices, applications, and cloud.
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Role of Cloud Computing in IoT:
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We know that the Internet of Things (sensors, machines, and devices) generate a huge amount of data per second. Cloud computing helps in the storage and analysis of this data so that enterprise can get the maximum benefit of an IoT infrastructure. IoT Consulting Services should connect and allow communication between things, people, and process, and cloud computing plays a very important role in this collaboration to create a high visibility.
IoT is just not restricted to functions of systems connectivity, data gathering, storage, and analytics alone. It helps in modernizing the operations by connecting the legacy and smart devices, machines to the internet, and reducing the barriers between IT and OT teams with a unified view of the systems and data. With cloud computing, organizations do not have to deploy extensive hardware, configure and manage networks & infrastructure in IoT deployments. Cloud computing also enables enterprises to scale up the infrastructure, depending on their needs, without setting up an additional hardware and infrastructure. This not only helps speed up the development process, but can also cut down on development costs. Enterprises won’t have to spend money to purchase and provision servers and other infrastructure since they only pay for the consumed resources.
IoT and connected devices use different communication and messaging protocols at different layers. While developing an IoT device, the selection of the protocol largely depends on the type, layer and function to be performed by the device. MQTT, XMPP, DDS, AMQP, and CoAP are a few of the widely used communication protocols for the IoT application layer. Let us understand each of them in detail.
In today’s time, networking with smart devices and IoT is increasing largely due to the ongoing technological revolution across the globe. People are increasingly using IoT and connected devices to automate industrial operations, control city traffic, track health, control home appliances, manage the fleet of vehicles, etc. Smart devices like phones, wearable devices, kiosks, appliances, and automobiles use the internet to connect with other devices and exchange information and data with servers to perform different operations.
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There are two ways these devices can connect to the internet. Some devices may connect through a gateway, while others may have network capability built into the devices itself. It is interesting to note here that for establishing the connection with the internet, these devices use messaging and communication protocols at each layer of the Open Systems Interconnection (OSI) model. Depending on the function of the device, the communication protocol at each layer varies.
*IoT Topology
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IoT devices work by fetching data from users, either through input devices such as touch screens or sensors used for motion detection, temperature, humidity, pressure, etc. This data is then sent to the data servers for storage and processing, and the resulting information is provided to the end user devices for analysis and control.
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To understand this, let us consider an example of a Smart Home setup. A typical smart home consists of devices like thermostat, door sensor, smart bulbs, smart refrigerator, smart TV, surveillance systems, etc. These devices are connected to the internet directly or to the gateway, which is further connected to the end user’s smartphone, mobile application or data center and vice-versa.
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Why RDM Remote devices management is used
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IoT Protocol Stack**
There are many protocols used in an IoT ecosystem at different layers of an OSI Model. However, the usage of a protocol is based on the type of application and its functionality. Usually, it is preferred to use low-powered protocols like 6LoWPAN, Bluetooth BLE, ZigBee, etc. Another deciding factor in choosing a protocol is the distance range for the communication of the IoT devices i.e. in inches or meters or miles.
When it comes to selecting a protocol for the application layer of the IoT system, there are several protocols available. However, the most common types of IoT application protocols include, MQTT, XMPP, DDS, AMQP, and CoAP.
MQTT (Message Queue Telemetry Transport)
MQTT is a machine-to-machine (M2M) protocol. It is a publish-subscribe-based messaging protocol, used to communicate device data to the servers. The main purpose of MQTT is to manage IoT devices remotely. It is mainly used when a huge network of small devices needs to be monitored or managed via Internet i.e. parking sensors, underwater lines, energy grid, etc.
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The MQTT messages are sent asynchronously through publish-subscribe architecture. The messages are encapsulated in several defined control packets, which are designed to minimize the network footprint. Listed below are a few MQTT protocol control packets:
An MQTT control packet is formed as shown in the figure below.
It should be noted that not all control packets have the variable headers and payload. A payload can be up to 256 MB. The small header overhead in MQTT makes this protocol appropriate for IoT.
Today, traditional businesses are getting prepared for disruption from digital natives. According to IDC, global spending on digital transformation will be $2 trillion by 2022. As digital and physical worlds are merging at an alarming and accelerated pace, businesses need to start thinking about how to maximize the opportunities by leveraging new age digital technologies.
Introduction
Today, traditional businesses are getting prepared for disruption from digital natives. According to IDC, global spending on digital transformation will be $2 trillion by 2022. As digital and physical worlds are merging at an alarming and accelerated pace, businesses need to start thinking about how to maximize the opportunities by leveraging new age digital technologies.
Digital Transformation is setting new standards for business growth. It is not just about incorporating newer technologies into business; it’s a digital disruption, which requires restructuring everything in the business process. As the numbers of connected devices from smartphones to cars to home automation to industrial automation to smart cities and its connection to humans are increasing, organizations that deliver digitally transformed products or services are gaining a competitive advantage over others in the market.
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As per IDC, 32% of new technology investments will be driven by digital transformation, and by 2020, 60% of all enterprises will be in the stage of implementing a digital transformation strategy
By adopting smart technologies and transforming the legacy business processes, businesses will become more capable in improving customer experience, earn more trust and, as a result, increase their profit.
So what is a digital transformation? ― It is about rethinking the products and processes, digitalizing systems, and delivering highly connected and contextual experiences for the end consumers. It’s more about discovering ways by which companies can provide better digital customer experience.
Emerging technologies such as IoT, Artificial Intelligence, Virtual Reality, Augmented Reality, Big Data, Cloud Computing, and Machine Learning are predominantly changing the way businesses operate.
It’s natural to go gung-ho for advanced digital technologies, but it is equally essential to know about the digital transformation prerequisites, key drivers, complex challenges, strategies, roadmap, framework, principles, success steps, investments, ROI and benefits.
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Why Digital Transformation is essential for your organization?
Digital innovation brings technological disruptions that lead to a complete transformation. Digital transformation is essential because it provides a valuable opportunity for business operations to move from legacy manual processes to digitally automated process, enabling leaders to focus on broader business opportunities. The business that has incorporated digital technology have often experienced the following:
Significant increase in sales, and hence more revenue generation
Significant customer acquisition, retention, and satisfaction
Product and process improvement
Employee satisfaction
Increase design and engineering productivity
Improved product quality
Businesses, of all sorts, are creating cleaver, compelling, and disruptive ways to utilize technology for customer delight. Netflix is an excellent example of digital transformation. Netflix started as a mail-order DVD distributor and disrupted the video rental market. Later, it came up with wide-scale video streaming services. Today, Netflix has taken over traditional television cable service provider and by offering on-demand content like movies, series, and videos at very competitive prices. Netflix effectively leveraged the technologies to get insights into customer preferences and provided the on-demand content to the end-user.
Key Stats
The worldwide spending on digital technologies will be almost $2 trillion in 2022. (Source-IDC).
The connected cars market is expected to reach $225.158 million by 2025, registering a CAGR of 17.1% from 2018 to 2025 (Sources: Allied Market Research)
The highly digitized semiconductor industry is expected to spend around $120 billion by 2022.
(Sources: Strategy& Innovation database, 2017 Global R&D funding, Expert interviews, Strategy& analysis).
Key Drivers for Digital Transformation
The rapidly changing consumer preferences, technology, and competition gives rise to the enormous market for digital transformation. Consider an example of Uber which has completely dominated the transportation sector, forcing other taxi service providers to discover ways to incorporate similar online app-based ride experience, ride-sharing, car on rent or other on-demand services into their business. The factor behind this transformation push is technological innovation from digital-native companies like Uber.
The following are drivers of digital transformation.
1. Increasing expectation for personalized experiences
With the evolution of smart technologies, customer preferences have been evolving continuously. Today, customers are preferring product and services that are available 24/7 and that can be access from anywhere. With advent of digital technologies businesses are fulfilling the customer expectations by building smarter products that can be customized further based on specific requirements.
Introduction of disruptive technologies
The pace of innovation is accelerating with disruptive technologies. Internet of Things, Artificial Intelligence, Machine Learning, and Big data analytics are driving the market today. All these digital technologies are forcing businesses to change across every sector in the economy.
Rise in competition for digital technologies
Today, every other organization is bringing digital change in their business process as the competition level for adopting digital technologies and providing customized solutions are increasing rapidly. As per Research & Market, the global digital transformation market is expected to grow from US$ 445.4 billion in 2017 to US$ 2,279.4 billion by 2025 at a CAGR of 24.3% between 2018 and 2025.
Digital Transformation Challenges
Change comes with its own set of challenges. Digital transformation is painful when not understood properly. It becomes a complex problem when the leadership team doesn’t know what change it will bring or if the goals aren’t clearly defined.
Also, many organizations are not ready for this new reality. The legacy business models, outdated technologies, operations, resources, and skills don’t allow much scope for any new transformations.
The reason behind this could be due to the challenges it poses to their job and fear of failures. To deal with this, organizations should have an effective digital learning model in place to enhance their capabilities in implementing, adapting, and evolving with digital technologies. It is essential to empower the workforce with digital resources to carry out a successful product transformation.
Technology Integration Challenges
During digital transformation, you’re bringing in new digital technology to a legacy setup, and replacing outdated and non-performing processes. You’re utilizing the existing system to integrate with digital technology for bringing digital transformation. The technology integration for new process causes delays as employees face further technical training and getting accustomed to the new management techniques. Another challenge here is the cost and technical expertise required for integrating the legacy technology with the new one.
The Data Challenges
The data are the fuel for digital transformation. There are several challenges associated with data handling during the implementation, from data capture to storage to analysis. Organizations are finding many difficulties as they try to learn how to gain valuable insights and competitive advantages from it. The need is to gather critical data, store for a long time and use process it to produce results.
Digital Transformation Roadmap
The digital transformation strategy should clearly define and talk about the business process change, cultural change, technology change, and legacy product or service change. During updating the existing systems or adopting cutting edge technologies, enough attention must be given to the changes that will impact the business culture and the business processes.
Some of the critical steps to take for a successful digital transformation initiative:
Keep digital transformation on top priority while crafting the business strategy
Collect and utilize data and analytics to make business decisions
Adopt a company-wide approach towards successful digital transformation
Maintain the combination of both people and technology to smoothen the digital transformation process
Monitor and control the process as and when required
For becoming successful in digital transformation, companies need to not only invest in technologies but also rethink on creating new business models, invest in digital talents, develop digital measurement matrices, and integrate automation into the workforce.
Create a Digital Business Models-. Create a lean strategic approach that helps to plan operations and support function activities. Always focus on getting relevant data and make business decisions based on data analytics. Partner with digitally capable firms and invest in emerging technologies such as IoT, ML/AI or Cloud.
Invest in Digital Talent and Skills- Is your team digitally sound? Assess the digital capabilities of the team and based on results, create a digital talent pool roadmap. Drive an organization-wide digital talent campaign and improve the skills of the workforce.
Understand and leverage data– Do not underestimate the power of data. Data are critical element for business decisions. Perform analytics on customer data, operational data, performance data, technical data, and non-technical data. Take decisions for the future, based on data analysis and business forecasting.
Automate workforce– Know the importance of automation in work culture. Automate the business process for efficient and accurate work. Automation helps in cost reduction, increasing productivity, efficiency, and performance of the team.
Digital Maturity Plan
What is digital maturity? ―Digital maturity is the ability of a company to respond appropriately to the emerging digital competitive environment. In digital journey, business assess their current capabilities that exist within an organization and help them to be clear where these need to transform or improve. In order to bring the digital change into your organization, follow the 3D approach of digital transformation.
3D Approach to Digital Transformation
tain the combination of both people and technology to smoothen the digital transformation process
read the full bloghere — https://www.einfochips.com/blog/a-blueprint-on-digital-
Kubernetes is increasingly becoming the de-facto standard with more software & applications workloads moving into containers. Kubernetes has capture the cloud market by storm through the implementation of strong infrastructure development. It makes deploying and managing the app easier and improve reliability and reduce the time you need to spend on DevOps.
In today’s economy, most software businesses are looking to provide a new high-performing application along with a seamless customer experience. Kubernetes is one of the emerging platforms that enables companies to run and manage containerized applications globally. Before we deep dive into the details of Kubernetes lets understand first what it means.
What is Kubernetes?
Kubernetes (also known as k8s) is an open-source platform (developed by Google) for managing containerized applications across multiple servers, providing basic frameworks for deploying, maintaining, and scaling applications.
According to a report by Gartner, by 2022 more than 75 % organizations globally will be running containerized applications.
Kubernetes can run within the public cloud or on premise environment. Cloud computing service providers like AWS, Microsoft Azure, and GCP provides managed solutions using Kubernetes that enable customers to start up K8s apps fast and operate efficiently.
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So how Kubernetes is benefiting large enterprises?
Here are five primary business capabilities that are driven by Kubernetes and its benefits for large enterprises
Faster app development/deploymentReducing resource costsWorkload scalabilityMulti-cloud flexibilityEffective cloud migration
1. Faster app development/deployment
Kubernetes makes use of micro-services as its primary key point for deploying the applications. Using Kubernetes, you can split the IT team into smaller teams, where one will be able to focus on smaller services, and these teams will be able to perform well as they focus on a particular functional area resulting into saving a lot of time.
The APIs among these micro services reduce the sum to build and deploy cross-team communications. You can easily scale-up or scale down the application as per the requirement. Kubernetes allows access to storage from different providers like AWS and Microsoft Azure and it helps to communicate faster between the containers.
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Kubernetes considers the available resources and smartly schedules and tightly packs the containers. If the users of an app or software increases then it automatically adds more processing power so that more users can be active, which ultimately helps your developers to focus on other productive activities.
Kubernetes is not only helping in scaling up the infrastructure metrics but also helps in resource utilization metrics, and custom metrics to scale the process.
Read this full article here Microservices Architecture
Companies today, are increasingly moving their IoT systems to cloud to enhance the scalability and user-experience of the devices. Migration of IoT systems to cloud not only includes infrastructure migration, but also involves migration of operations to the cloud -- termed as CloudOps. Let us understand in detail about CloudOps in IoT.
In today’s time, the world is constantly moving towards ‘everything as a service’. Thanks to the Internet of Things (IoT) that is enabling faster connectivity and transformation in the digital space. The IoT ecosystem, which comprises devices, sensors, connectivity protocols, gateways, network infrastructure, web, and mobile applications is big now and set to become even bigger in the future. With so many connected devices and applications, the user experience and scaling of the system have become the prime differentiators for a lot of companies offering IoT products, platforms, and services. This is why, Cloud computing is widely getting adopted by companies to provide seamless user experience, achieve scale and ensure maximum uptime of the IoT devices in the connected environment.
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Companies today, are increasingly moving their IoT systems to cloud to enhance the scalability and user-experience of the devices. Migration of IoT systems to cloud not only includes infrastructure migration, but also involves migration of operations to the cloud -- termed as CloudOps. Let us understand in detail about CloudOps in IoT.
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In today’s time, the world is constantly moving towards ‘everything as a service’. Thanks to the Internet of Things (IoT) that is enabling faster connectivity and transformation in the digital space. The IoT ecosystem, which comprises devices, sensors, connectivity protocols, gateways, network infrastructure, web, and mobile applications is big now and set to become even bigger in the future. With so many connected devices and applications, the user experience and scaling of the system have become the prime differentiators for a lot of companies offering IoT products, platforms, and services. This is why, Cloud computing is widely getting adopted by companies to provide seamless user experience, achieve scale and ensure maximum uptime of the IoT devices in the connected environment.
Adopting cloud computing for IoT means companies need to move their entire IoT infrastructure, including operations to the cloud. In cloud migration of on-premise IoT applications, subsequent microservices architecture and DevOps process transformation in the cloud become an integral part of cloud operations. However, the major challenge most organizations face is running and managing these IoT operations in the cloud once the migration is complete.
Gone are the days when IT and data center teams used to monitor only applications and related servers, network, connectivity, etc. In an IoT cloud environment, monitoring edge devices like video nodes, home automation gateways, fleet management cameras, etc., along with related cloud services, microservices, containers, response times, live requests, configuration ease, dynamic storage, latency, availability, VMs, CPU utilization, database, cloud security, etc., become some of the additional parameters that need to be considered.
read more https://www.einfochips.com/blog/exploring-essential-cloudops-in-iot/
Heavy equipment represents a large list of heavy vehicles, engineering equipment, and bulky industrial machinery. Things or characteristics that one would expect from heavy equipment are oversized dimensions, long life expectancy, and improved equipment performance, as these machines are a fundamental part of the workflow process in many industries. Safety and efficiency are the key concerns for companies that extensively use such equipment.
Heavy equipment is mainly used extensively in industries such as construction, oil and gas, mining, forestry, energy, civil engineering, military engineering, transportation, and many others. Industrial heavy machines include construction equipment, wheel loaders, oilfield pieces, manufacturing equipment, earthmovers, hydraulic cranes, bulldozers, oversized trucks, forklifts, and more. Organizations rely on heavy machinery to speed up production and to avoid human errors or health risks.
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With developments in IoT, it is possible to decrease equipment downtime while improving the efficiency of the output. Companies that supply industrial machinery and components are seeing strong interest in connected machinery and components with IoT integration. IoT-powered asset management solutions offer a host of benefits, including predictive maintenance to prevent equipment failure, increased asset reliability, improved asset health, accident avoidance in the workplace, and downtime reduction.
Smart Asset Monitoring with IoT
Safety of personnel and assets, theft or pilferage of assets, accidents and resulting injuries, and bottlenecks in the supply chain are some of the common challenges that are prevalent in asset-intensive industries like manufacturing, utilities, construction. By improving visibility into day-to-day operations, replacing legacy systems with an integrated solution and automating manual processes, many of these challenges can be overcome.
read full blog https://www.einfochips.com/blog/how-iot-is-making-heavy-equipment-safer-and-more-efficient
Edge intelligence has the potential to transform the manufacturing industry. In fact, the process has already begun. Ranging from pipeline safety and smart metering to fleet management and warehouse management, intelligent edge solutions have already helped improve safety and efficiency, while delivering cost savings and improved user experiences.
In the era of digital transformation, smart technologies are revolutionizing most industries, and the manufacturing industry has not escaped the revolution. If you work in the manufacturing sector, it is likely that you are aware of the upcoming innovations that, smart manufacturing which will hold the largest technology market that will transform the way manufacturing operates.
Internet of Things developments is spreading like a wildfire across the market today and transforming how organizations and customers approach their workday around the globe. There no arguing the fact that the smart manufacturing sector provides a lot of scope of IoT.
Many manufacturing businesses are focusing on new and exciting technologies using IoT to create an intelligent, decision-making ecosystem of connected devices and things with proactive, autonomous and analytics capabilities, with the end goal of improving efficiency and productivity across the business. The sheer scale at which IoT is being implemented across the industry has led to the coining of a new term: IIoT (Industrial Internet of things).
Efficiency problems plague even the best manufacturing facilities leading to supply chain issues, productions losses, accidents, and more. With the advent of IIoT and related new technologies, it is possible to overcome these issues. Powered by the cloud, IIoT is already driving improved efficiencies within factories and throughout the supply chain by collecting the vast quantities of data from sensors in just moments.
However, gathering large chunks of data is just one part of smart manufacturing – smartness in this context is the ability to use that data effectively to improve efficiency. It is the ability to make accurate predictions by analyzing data and take automated decisions in real time. This is where Edge Intelligence holds the potential for transforming manufacturing.
How is edge intelligence making smart manufacturing possible?
The term ‘Edge’ is used for computing infrastructure that resides closer to the sources of data. This includes a range of connected devices, including sensors, motor drives, alarms and more. The term ‘IoT gateway’ refers to devices that are placed between the edge and the cloud – the IoT gateway serves as a connection point between the smart devices and sensors on one end, and the cloud and controllers on the other.
With more intelligence being shifted from the cloud to the edge, the role of the industrial IoT gateway will expand from being just a gateway to becoming an edge server integrated solution.
Edge Intelligence helps manufacturers to smartly process huge data sets generated by the sensors and turn it into actionable data which can be used for reducing commissioning time as well as accidents on site. Essentially, instead of sending all the data to the cloud, the edge device sensors process the data right at the source. This makes it possible for the sensors to enable real-time actions – incredibly useful in situations where even a delay of a few milliseconds can cause serious damage.
How can bringing AI and ML to the Edge benefit the manufacturing sector? Let’s take a look at a few examples.
1) Pipeline Safety
Pipeline safety is a primary concern for Oil and Gas manufacturers. IoT and edge computing technologies can help the industry deal with a number of challenges such as volatility of oil prices, pipeline safety, ensuring the safety of workers in the hazardous environment, monitoring remote assets and more.
Let’s consider the issue of pipeline safety. Pipelines are one of the most efficient ways of transporting large quantities of crude oil or natural gas. A number of factors can impact pipeline safety – human error, corrosion, metal loss, leakage or tiny cracks – which can lead to major breakdowns. Even a pinhole leakage, which can be easily missed during a virtual inspection, could become a serious issue over time.
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To inspect and detect the corrosion on the surface of the pipe carrying oil & gas, a high-speed robotic scanner works as a great solution. It uses ultrasonic sensors and P.I.G (pipe inspection gauges), which notify the system about corrosion related defects. Cameras on the robot scanner identify and capture the details of defects such as corrosion, cracks or dents. The analysis of this data at the edge provides insights that are used to prevent future breakdowns.
2) Smart Warehouse
The management can improve warehouse efficiency by tracking assets in real time; assets include a range of equipment (e.g. forklifts) as well as staff. With the real-time availability of up to date information about the items’ location and nearest available forklift, the order-picking process can be improved. An analysis of the information about forklift movements in the warehouse can provide insights into how the material should be placed to minimize the travel time of forklifts.
But that’s not all – edge intelligence can also help make warehouse safer. For example, every year around 34,900 workers are seriously injured while 85 lose their lives in forklift accidents. In this case, not only are the operators are in danger, other people working near the forklifts are at risk too.
Operator inattention is the common cause of forklift accidents and it is a preventable issue. Wearable wireless sensors can be used to monitor fatigue levels of operators, suggesting rest periods. All this data can be processed at the edge in real time and can help trigger actions to prevent accidents.
Wearable sensors and data transmitters can also track employee movement around the warehouse, which displays the distance and the number of people in a given work area. Wearable tag scans the signals from employees and when this signal is closer to a forklift, and the driver gets notified when someone is close to his or her work area. So with edge analytics, hazardous situations can be identified before they happen by providing alerts to equipment operators.
3) Smart fleet management
Fleet (vehicle) management can include speed management, driver management, fuel management, vehicle financing, vehicle maintenance, vehicle telematics (tracking and diagnostics) and health and safety management. Fleet management companies, using IoT and edge computing, can remove or minimize the risks associated with vehicle investment, which further improves productivity and efficiency by reducing their overall transportation and staff costs.
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In this case, using real-time data generated by edge devices which are fixed into vehicles – dashboard cameras, for example – can help the operator to monitor driver’s behavior in real time. This enables them to know where vehicles and drivers are at all times. By analyzing this data, potential problems can be identified/predicted and resolved before they become larger issues.
4) Smart metering
Traditional meters only measure total energy consumption but smart meters, which are internet-capable devices, record when and how most of the energy is consumed. Autonomous monitoring of electricity consumption needs a metering platform to record and process electric data.
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Smart metering benefits utility companies by improving the customer satisfaction. Smart meters make it possible, both for the provider and the consumers, to automate and improve energy conservation. As consumers get more control over their energy usage and are able to save more money, they are happier with the utility providers.
By using edge intelligence, smart meters also give power consumption visibility all the way to the meter and back. This allows the utility companies to optimize energy distribution and take real-time actions to shift demand loads. Complex event processing is also possible in this scenario – it can be achieved by grouping the appliances.
IoT Gateways are becoming an essential part in various smart grids solutions, across Industrial, Residential, and Transmission & Distribution projects. Gateways help in addressing energy conservation at both the consumer and transmission level. Here, we will discuss some of the unique features of IoT gateways like clustering, interoperability, security, and others
With ever increasing human population, urbanization, and connected digital lifestyle, many energy companies are now focusing on developing sustainable energy management and conservation solutions. Today, smart grid solutions or IoT solution for grid infrastructure is playing a major role in developing many use-case based energy conservation solutions, by connecting disparate platforms in home automation, building & infrastructure automation, and transmission & distribution systems.
An IoT gateway for a grid solution can quickly help in connecting and transitioning the existing devices infrastructure, even legacy systems, to securely connect to any smart grid infrastructure, thereby enabling a highly scalable solution for energy conservation projects.
IoT gateway enables a wide range of connectivity to HAN or BAN (Home Area Network or Building Area Network) protocols like ZigBee, Bluetooth, Wi-Fi, BACnet, and LAN. Devices or sensors can connect to the gateway which in turn connects to the cloud. This allows the user to access the sensor data remotely through their mobile devices from any location at any time.AMI (Advance Metering Infrastructure) / Smart meters are playing an important role in energy management of a grid system. It collects energy consumption data on real-time from devices, and this data is later analyzed by gateway that is connected to AMI via HAN. Gateway escalates necessary output or command message to the control system.
The message can be an alarm, HVAC control message or any other utility management commands. It enables communication between devices and AMI system. Combination of AMI connected to the HAN or BAN and an IoT gateway results in a smart grid system.It helps in analyzing energy utilization of each device, which aids the user in managing device up/down time. Users can access historical data from the cloud – insights such as which device consumed more data and at what time of the day, and accordingly they can optimize their consumption of energy.
IoT / Industrial IoT gateways provides utility companies with a broader view of their energy distribution patterns, by enabling high connectivity and real time analysis of resources.It enables to develop a Demand-Response mechanism for the utility providers to optimize energy distribution based on the consumption patterns.Collects data from all AMI systems that are connected to that utility provider and gives analytical results on high and low energy consumption periods. Accordingly, utility providers can utilize these insights from analytics to predict peak load times and enable dynamic pricing options.
