6 Myths About Industrial IoT Implementation Debunked

Industrial IoT Implementation

BehrTech Blog

6 Myths about Industrial IoT Implementation Debunked

The Internet of Things is ushering in the Fourth Industrial Revolution. While the need for digitalization is understood across-the-board, there are still many misconceptions that deter Industrial IoT implementation. Many organizations are postponing their IIoT initiatives or hesitate to move beyond pilots due to complexity and cost concerns.

Preparing for the worst isn’t necessarily bad, but you might be overcalculating the risks of IIoT and undermining its true value. Shying away from IoT implementation based on false assumptions won’t help your bottom line and competitive edge. To help you build a more accurate picture, this week we debunk 6 common myths around IIoT deployments.

IIoT Implementation

Myth #1: IIoT Always Means Cloud (Internet)-Connected

The cloud is that buzzword hovering around most IoT or Industrial IoT discussions. Without doubt, the cloud has its perks and a profound position in the IoT marketplace. It provides cost-effective, ubiquitous infrastructure for massive data storage and management. Cloud computing incorporating advanced machine learning algorithms can even identify trends in processes and equipment operations to anticipate and prevent future failures.

Having said that, the cloud is by no means a must in an IoT implementation. Despite their benefits, cloud solutions may not be a preferred option for many industrial companies. This is because a large number of legacy industrial systems have only limited security features, making them an easy target for cyber hackers when connected to the Internet. Besides cyber-security risks, data privacy, increased latency and uncertain service uptimes are other top concerns of third-party managed clouds.

With numerous wireless vendors offering cloud-integrated solutions, it seems the cloud is an indispensable part of Industrial IoT implementation. The truth is, the most versatile IIoT architecture renders this decision to end users, letting them employ a backend system that best suits their business requirements. Operational data can be relayed to an on-premises historian and data center or a cloud-based analytics platform – depending on users’ needs. IIoT is about increased control and visibility of industrial operations to augment operational efficiency, safety and sustainability. This should never come at the costs of security and data authority.

Myth #2: IoT-Enabling Legacy Systems Is Highly Complex and Involves Production Downtime

Born during the Third Industrial Revolution, Programmable Logic Controllers (PLCs) are at the heart of industrial automation systems. Though excelling at real-time, localized tasks, these control hubs – designed in the early 2000s – aren’t meant to be connected to the outside world. The majority of older PLCs come with a plethora of proprietary serial protocols only intended for closed-loop control processes. Newer PLCs may come with Ethernet connection, but many hostile industrial environments are prohibitive for hardwiring.

Due to these communication challenges, manufacturers tend to think that IoT enabling legacy PLCs and industrial systems is extremely arduous, if not impossible. It’s common to picture a daunting process with burdensome hardware changes, wiring and weeks of production shutdowns. The fact is, emerging plug-and-play connectivity is making IIoT implementation in brownfield plants much more a reality.

Such a solution can interface with legacy PLCs using automation-specific protocols to extract critical data points without any hardware modifications. Providing a robust radio link, it can then wirelessly transfer data to a central management system, eliminating any wiring requirements. As such, costly production downtime is simply not part of the process.

Myth #3: IoT Is Only About Millisecond-Latency Automation Networks

Manufacturers often apply the conventional, automation-centric mindset to interpret IoT and its potential value. Many envision digital factories as a new generation of automation facilities – fully equipped with next-gen manufacturing lines and robotic machinery that can communicate data in millisecond latency. While enhanced real-time automation is part of the story, it surely isn’t the single facet defining our next industrial revolution.

The central value around IIoT is unprecedented visibility into existing processes and equipment that empowers strategic decision-making. Oftentimes, such visibility comes from granular sensor networks capturing asset, process and contextual data. Think of examples like workers’ wearables, pipeline sensors and environmental sensors. By timely notifying conditions that can disrupt operations and threaten worker’s health, remote monitoring networks are a core pillar of IIoT deployments to enhance plant safety and productivity.

Rather than high-bandwidth, time-sensitive communications, IIoT sensor networks mostly pertain to sending small bursts of telemetry data every few minutes or only when abnormalities are identified. Data sent too frequently, on the contrary, can be useless and burden the backend system. What really counts is network coverage, reliability and scalability alongside the ability to operate on independent batteries for years. Automation-oriented Ethernet infrastructure can’t keep up with these requirements.

Myth #4: IIoT Implementation Is Too Capital Intensive

The need for a new wireless communications architecture often induces the idea of significant upfront investment that deters IIoT adoption. However, as soon as you start looking at technological options available today, you’ll realize that building an IIoT infrastructure doesn’t necessarily cost a fortune. A new robotic system can cost hundreds of thousands of dollars upfront – not to mention the complex and expensive setup and maintenance process. In direct comparison, a wireless low-power IIoT sensor network can be deployed at a fraction of both capital and operational expenditures (CAPEX & OPEX).

Besides the much-reduced sensor cost today, new wireless technologies like Low Power Wide Area Networks (LPWAN) provide highly cost-effective connectivity for factory-wide sensor networks. With a scalable solution, you can also minimize expensive infrastructure (i.e. base stations) while addressing multiple applications and challenges simultaneously. This, in turn, streamlines complexity and accelerates Return-on-Investment (ROI).

Myth #5: IIoT Has Little Immediate Value

Even when an IIoT investment is comparatively affordable, manufacturers may still think it isn’t worth it. This is due to the common notion that IIoT has little immediate value and is just an optional add-on to daily operations. However, knowing that the total estimated cost of industrial downtime tops $50 billion annually, may change your mind.

By unlocking data from systems previously functioning in an encapsulated manner, IIoT helps manufacturers break down plant data silos. Enhanced asset and operational transparency greatly facilitate troubleshooting and maintenance activities while eliminating manual tasks. This will have an immediate impact on cost savings and overall equipment effectiveness by reducing machinery and production downtime.

Myth #6: IIoT Will Eventually Replace People

IIoT reflects a paradigm shift in industrial operations and the required expertise. Certain manual tasks will be automated for enhanced productivity, but this doesn’t mean the need for manpower will fade away. On the contrary, a digital factory is only as smart as the people who operate it. To secure and translate Big Data into business intelligence, new job domains like data scientists and security engineers will be critical. Existing jobs like machine operators will continue to evolve with new skill sets. Human intelligence is the brain behind Industrial IoT implementation and no machine can be as flexible as humans themselves.

It’s also important to note that IIoT frees worker from repetitive, monotonous tasks to focus on more rewarding, higher-value ones. Likewise, one of its ultimate goals is to create a safer and healthier work environment for employees. As such, rather than being viewed as an employment threat, IIoT should be seen as a means towards future worker-centric smart plants.

As with any previous industrial revolutions, IIoT implementation does not come without challenges. However, make sure the misconceptions aren’t diverting you from the reality. Accurately assessing how IIoT can tackle your business challenges and measure it against potential costs will be key to a successful deployment.

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Sub-GHz vs 2.4 GHz ISM Band: 5 Implications for Your IoT Deployment

sub-GHz vs. 2.4 GHz

BehrTech Blog

Sub-GHz vs 2.4 GHz ISM Band: 5 Implications for Your IoT Deployment

When assessing different wireless solutions for your IoT deployment, you may be surprised to discover that most technologies are adopting license-free Industrial, Scientific and Medical (ISM) frequency bands for their operations. Without the complex licensing processes and hefty fees of the licensed bands, the license-free spectrum has been a preferred choice for many developers. While there are various ISM bands available today, the decision often boils down to sub-GHz vs 2.4 GHz frequencies.

If you think the difference between these two groups of ISM frequency bands only matters to wireless system developers, think again. For all IoT adopters, being able to distinguish between sub-GHz and 2.4 GHz ISM bands is a major help in your wireless technology decision. This is because the operating frequency impacts the ways in which a radio system performs in key network criteria.

In this blog, we outline 5 major distinctions between sub-GHz and 2.4 GHz to be measured against your network priorities.

1. Sub-GHz ISM Bands = Much Longer Range

As the wavelength is inversely proportional to frequency, sub-GHz waves are much longer than the 2.4 GHz ones. A major advantage of the longer wavelength is that signals can better penetrate through walls, trees, buildings and other structures along the propagation path. On top of that, longer waves are less susceptible to reflection and can bend farther around solid obstacles (i.e. diffraction). Wavelength is also inversely proportional to free space path loss, meaning longer radio waves can travel farther in open areas. Simply put, radio signals in sub-GHz ISM bands offer a better range and can operate more reliably in structurally dense environments.

2. Sub-GHz Signals Experience Less External Radio Interference

Due to its free access, the unlicensed spectrum is filled with multiple co-existing radio technologies. In comparison, the 2.4 GHz ISM band is much more crowded because of legacy use. Wi-Fi hubs, Bluetooth-enabled devices, cordless phones, welding equipment, RF lighting and microwave ovens are just a few examples. The high radio traffic and electromagnetic noise in the 2.4 GHz airways can greatly dampen the reliability and scalability of the IoT network. Saturated 2.4 GHz channels in your facility are not recommended for your IoT deployment.

3. Systems Using Sub-GHz ISM Bands are Often Designed for Lower-Bandwidth Transmissions

Bandwidth represents the range between the upper and lower frequency limit used for transmitting a signal. The more information a signal carries, the more bandwidth it requires. In radio communications, high bandwidth is associated with a high data rate, as you can send more data per time unit. Generally, higher carrier frequencies allow for more bandwidth usage due to larger available spectrum resources, and vice versa. As a result, radio systems in the 2.4 GHz ISM band are often designed for higher-throughput data communication compared to sub-GHz systems.

4. Technologies Using Sub-GHz ISM Bands Are More Power Efficient

Because they use less bandwidth and lower data rates, systems operating in sub-GHz ISM bands offer the benefit of lower power consumption. Signals requiring less bandwidth result in lower thermal noise which in turn, provides better receiver sensitivity (the minimum power level at which a receiver can detect a signal). All things being equal, systems with higher receiver sensitivity require less transmission output, resulting in less power consumption.

Another aspect that favors the power efficiency in sub-GHz solutions is network topology. Thanks to the better range performance (i.e. many kilometers), a sub-GHz transmitter node can send a message directly to a remote receiver using the one-hop star topology. On the other hand, systems in the 2.4 GHz ISM band often resort to a relaying mesh topology to compensate for their short physical range (i.e. few to hundred meters) and extend the data communication distance. The fact that a node must actively stay awake to relay messages through them greatly increases power consumption and thus reduces battery life in 2.4 GHz mesh networks.

5. Systems Using Sub-GHz ISM Bands Are Likely to Entail Less Infrastructure Cost

In terms of infrastructure cost, both options have their benefits, but sub-GHz networks might be the winner here. As antenna length is a function of wavelength, 2.4 GHz solutions require smaller and less expensive antennas for their operations. However, in long-range applications, 2.4 GHz mesh systems often demand extra repeaters to ensure sufficient coverage. A scalable sub-GHz network, on the contrary, requires as few as one base station to cover the same area and number of sensing devices.

Key Takeaways

To wrap it up, both 2.4 GHz and sub-GHz ISM frequency bands have their own pros and cons and are geared for different applications. 2.4 GHz RF is generally a better fit for use cases requiring high data rates within a smaller network environment, such as camera surveillance, personal health and fitness, and some consumer applications. On the other hand, in low-throughput, latency-tolerant scenarios where priorities are placed on range, power efficiency and scalability, sub-GHz RF would be more feasible. This refers to the majority of batter-powered, remote monitoring use cases in industrial and commercial marketplaces.

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[Infographic] Consumer vs. Industrial IoT: What You Need to Know

Consumer vs. Industrial IoT

BehrTech Blog

Consumer vs. Industrial IoT: What You Need to Know

Believe it not, the Internet of Things (IoT) is permeating every walk of life and step-by-step disrupting the way our world is functioning. IoT applications exist across multiple market verticals – from healthcare, mobility and logistics to manufacturing, utilities and agriculture. In general, the overarching IoT ecosystem can be broken down into two major subsets – Consumer IoT and Industrial IoT.

While sharing basic similarities in definition, there are significant differences as to how a Consumer vs. an Industrial IoT network is implemented in the real world. A lot of these differences have to do with the demanding and complex industrial environments hardly encountered by consumer devices. Industrial assets and systems are often situated at remote, physically challenging locations like underground, offshore or over elevated terrains – with limited or no power supply. On top of that, a plant environment is characterized by extreme humidity and temperatures alongside dense concrete and steel structures that hinder effective radio communications.

A Consumer IoT network typically entails few consumer devices, each of which has a limited lifetime of several years. On the other hand, an Industrial IoT network must connect hundreds, if not thousands of data points to support operations of expensive industrial equipment over many decades. The scale of impact during network breakdowns also greatly differ. Simply consider when your Fitbit device malfunctions vs. when fill-level sensors on material tanks fail to timely transmit data, resulting in long production halts. When designing a versatile IoT architecture, product managers need to factor in these fundamental distinctions to decide the right set of technologies.

The infographic below recaps basic differences of Consumer vs.Industrial IoT – from market value, major verticals and applications to network considerations, network requirements and viable wireless options.

Consumer vs Industrial IoT

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What Is MQTT And Why You Need It In Your IoT Architecture

MQTT in the IoT architecture

BehrTech Blog

What is MQTT and Why You Need It in Your IoT Architecture

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If you play in the IoT space, you may have heard of the MQ Telemetry Transport (MQTT) protocol. In addition to being used as an underlying communications protocol for IoT and Industrial IoT architectures, MQTT is used in smart home automation systems alongside cloud platforms such as Microsoft Azure, AWS and IBM Watson. Facebook also uses MQTT as a communication protocol for its Messenger and Instagram platforms.

The Industrial Internet of Things (IIoT) can be loosely defined as a system of sensors and other devices interacting with industrial and manufacturing systems all in an effort to enhance business operations. Industries like manufacturing, mining, oil & gas and agribusiness, to name just a few, deploy massive numbers of sensors. These sensors in turn send critical telemetry data to analytics engines, where the data is analyzed for trends and/or anomalies, enabling organizations to better understand and improve their operations.

In environments using Low Power Wide Area Network (LPWAN) solutions, sensor data is sent over wireless radio transmissions where it is received by one or more central base stations. This data, small as individual packets but massive when aggregated together, is then sent to analytics and visualization tools whether in the cloud or on-premises. That’s where MQTT comes in. Residing on top of the TCP/IP network stack, MQTT is a lightweight publish/subscribe messaging protocol designed for low-bandwidth, high latency, unreliable networks. MQTT’s features make it an excellent option for sending high volumes of sensor messages to analytics platforms and cloud solutions.

[bctt tweet=”As organizations migrate to LPWAN, MQTT will prove to be an excellent option for sending high volumes of sensor messages to analytics platforms and cloud solutions.”]

History of MQTT

MQTT was invented in 1999 by engineers Andy Stanford-Clark and Arlen Nipper, as a method of allowing pipelines in the oil and gas industry to communicate with Supervisory Control and Data Acquisition (SCADA) systems. At the time, these systems used disparate, proprietary protocols, and, as such, were not able to communicate with each other. Adding MQTT capabilities helped overcome inter-communication problems. In addition to interoperability, the original goals for the protocol were that it should be lightweight, bandwidth efficient, data agnostic and simple to implement while offering quality-of-service data delivery.

Publish/Subscribe Model

Unlike the traditional client-server model, in which a client communicates directly with an endpoint, MQTT clients are split into two groups: A sender (referred to as a publisher in MQTT) and a consumer that receives the data (an MQTT subscriber). The publisher and the subscriber do not know anything about each other, and, in fact, are never in direct contact with each other. A third component (an MQTT broker), acts like a ‘traffic cop’, directing messages from the publisher to any end points acting as subscribers.

MQTT in the IoT architecture

MQTT Topics

Messages make their way from a publisher, through a broker, to one or more subscribers using topics. Topics are hierarchical UTF-8 strings. Each level in a topic is delimited by a forward slash. Every message from a publisher must include a topic. To receive the published message, the entity that consumes the message must subscribe to the same topic. A broker sends the message it receives only to those clients that have subscribed to the same topic. Examples of topics are:

building1/shop-floor/temperature
location/field1/row10

MQTT and LPWAN

In environments using LPWAN solutions such as MIOTY by BehrTech, base stations perform the role of MQTT publisher. When a base station receives a message from a sensor, the base station publishes the message to the MQTT broker on behalf of the sensor. The broker then sends the message over TCP/IP to whatever device or devices that have subscribed to the topic.

MQTT in the IoT Architecture

MQTT is natively supported on BehrTech base stations. MQTT brokers and mappings for publishing data are configured with ease. Our out-of-the-box Azure integration also uses MQTT in its underpinnings. Another way in which we use MQTT is through the Node-RED programming tool. Performing the role of the subscriber, Node-RED takes incoming sensor data, processes it and sends it to visualization dashboards. As the published messages from the base station continue, Node-RED dashboards are updated on the fly.

Going forward, as organizations continue to move to LPWAN solutions in order to take advantage of its many benefits, the popularity of MQTT in the IoT architecture will grow as well.

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A New Approach to Indoor Localization in Large-Scale Environments

Indoor Localization

BehrTech Blog

A New Approach to Indoor Localization in Large-Scale Environments

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Data on the location of critical equipment and workers, provides powerful insights to optimize asset management and worker safety. Nevertheless, effective indoor localization, especially in large-scale environments, has been a bottleneck in available tracking solutions.

The Global Positioning System (GPS) and many other terms like Navstar, Glonass, Satellite Location and Position Tracking are buzzwords we hear every day.

GPS provides services like asset tracking, fleet tracking, family and even pet tracking that have become essential to our daily life. These services are constantly evolving. UBER is a great example using GPS as a key enabling technology for its innovative service offerings in over 500 cities now globally.

Unfortunately, despite all of its unique power and global availability, GPS is not feasible for indoor location tracking. This is because it doesn’t have the capability to receive satellite signals in indoor environments or provide location calculations independently when no signal is available.

So, what if you’re looking for a commercial-grade indoor asset tracking solution? What if you need to track medical equipment in a large hospital, locate a tool in a large warehouse, or keep an eye on mining workers when moving in underground mines where GPS is out of reach?

Several technologies exist for asset tracking and positioning in indoor locations. However, these solutions come with multiple challenges, especially when implemented in a large-scale environment.

[bctt tweet=”Providing unprecedented range, LPWAN has the potential to replace Wi-Fi and BLE for indoor positioning in geographically dispersed, challenging environments.”]

Challenges of Existing Indoor Localization Solutions

1. Proximity-Based Indoor Asset Tracking

Asset tracking solutions that rely on RFID and BLE Low Energy (BLE) have been around for some time. These solutions incorporate RFID tags or BLE beacons attached to the devices and communicate their ID data to a nearby hard-wired receiver. As RFID and BLE are very limited in coverage, these systems require a high density of receivers/sensing equipment. This quickly inflates infrastructure costs, not to mention the significant hassle of wiring a receiver every few meters in large-scale facilities.

Wi-Fi beacons/tags are another option, but the Wi-Fi range is also very constrained. A single Wi-Fi Access Point or Router usually covers a small area of up to 400 sq ft only, depending on the precision level needed. Also, Wi-Fi-enabled tags are very power-hungry compared to BLE, which makes it impractical for tracking of small devices.

Indoor Localization
Proximity-based Indoor Tracking

2. Trilateration-based Indoor Positioning Systems

Indoor Positioning Systems (IPS) using Wi-Fi or BLE and trilateration technologies are an alternative for indoor localization. These solutions analyze the Received Signal Strength Indicator (RSSI) of each signal to estimate the distance between a device and a Wi-Fi/BLE sensing equipment (RSSI is inversely proportional to distance). Trilateration algorithms are then applied to locate the device by coordinating its distance data from three or more sensing points.

There are generally two scenarios for IPS solutions using Wi-Fi or BLE. In the first scenario, a user device, often a mobile phone, picks up signals from multiple access points or beacons and transfer these signals to the trilateration server. This approach is often applied with people tracking and navigation where typically every user has a smartphone.

Indoor Localization
Trilateration-based IPS Scenario 1 (BLE example)

In the second scenario, a Wi-Fi tag or BLE beacon sends signals to multiple hard-wired receivers, which then relay received signal strength values to the trilateration server for location calculation. This scenario is more relevant for asset tracking applications where you can’t equip every asset with a smartphone. However, similar to proximity-based tracking, the major challenge is the high concentration of hard-wired receivers is required, especially in large indoor facilities.

Indoor Localization
Trilateration-based IPS Scenario 2 (BLE example)

Another major pitfall of all Wi-Fi/BLE-based IPS solutions is the labor-intensive and costly calibration process. Due to the random characteristics of indoor signal propagation, calibration is required in the initial installation to collect RSSI samples and build a radio map (i.e. fingerprint) of a given area. Given the short range of Wi-Fi and BLE, RSSI samples have to be gathered every few meters, which is a major undertaking in vast areas. Also, for worker safety applications in challenging environments like underground mines, Wi-Fi and BLE signals are very unreliable.

Could LPWAN Be the New Answer to Large-Scale Indoor Localization?

So, what type of solution offers a cost-effective, practical and easy to install indoor localization solution in large-scale, long-distance applications? The answer could be Low-Power Wide Area Networks (LPWAN).

Today, LPWAN technology is regarded as a key enabler of the Internet of Things (IoT). Whether tracking parts, people, or equipment, LPWAN is driving IoT advancements with no trade-offs in battery life or costs for improved range and much greater reliability.

Providing unprecedented, multi-kilometer range, LPWAN is potentially the only solution able to cover an entire factory, warehouse, hospital or a mine shaft. As such, LPWAN can potentially replace Wi-Fi and BLE for indoor positioning in geographically dispersed, challenging environments.

How can you build a robust, real-time Indoor Positioning System with a cutting-edge LPWAN technology? At its core, the solution architecture resembles the second scenario of WiFi/BLE-based IPS. There are two major components involved: LPWAN radio equipment delivering robust, wireless indoor connectivity and coverage, and a positioning server running trilateration algorithms.

LPWAN gateways pick up signals from a low-cost LPWAN transmitter attached to an asset or carried by a worker, and then relays the RSSI data to the positioning server. Thanks to much better range and penetration capability, an LPWAN-based IPS requires only a few gateways to cover an entire industrial plant or commercial building.

Indoor Localization
LPWAN-based Indoor Localization Architecture

Indoor tracking solutions with LPWAN do not require every asset and worker to have an expensive, battery-hungry Internet-connected device like a smartphone or tablet. What’s more, since only a few gateways are needed, the expensive and complex wiring process can be minimized.

Compelling LPWAN-based IPS use cases include worker safety and theft prevention of critical assets in vast industrial and commercial facilities, where sub-meter precision is not required.

Wrapping Up

There are many different tracking solutions and technologies in the market today. However, when factoring in cost as well as ease of implementation and management, LPWAN could be the most viable option. Furthermore, some LPWAN solutions, including ours, work on the principle that the data is the sole property of the customer and should not leave the premises. This makes LPWAN even more attractive for industrial and commercial applications where security and data privacy are a top priority.

 

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6 Leading Types of IoT Wireless Technologies and Their Best Use Cases

IoT Wireless Technologies

BehrTech Blog

6 Leading Types of IoT Wireless Tech and Their Best Use Cases

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The Internet of Things (IoT) starts with connectivity, but since IoT is a widely diverse and multifaceted realm, you certainly cannot find a one-size-fits-all communication solution. Continuing our discussion on mesh and star topologies, in this article we’ll walk through the six most common types of IoT wireless technologies.

Each solution has its strengths and weaknesses in various network criteria and is therefore best-suited for different IoT use cases.

IoT Wireless Technologies

1. LPWANs

Low Power Wide Area Networks (LPWANs) are the new phenomenon in IoT. By providing long-range communication on small, inexpensive batteries that last for years, this family of technologies is purpose-built to support large-scale IoT networks sprawling over vast industrial and commercial campuses.

LPWANs can literally connect all types of IoT sensors – facilitating numerous applications from asset tracking, environmental monitoring and facility management to occupancy detection and consumables monitoring. Nevertheless, LPWANs can only send small blocks of data at a low rate, and therefore are better suited for use cases that don’t require high bandwidth and are not time-sensitive.

Also, not all LPWANs are created equal. Today, there exist technologies operating in both the licensed (NB-IoT, LTE-M) and unlicensed (e.g. MYTHINGS, LoRa, Sigfox etc.) spectrum with varying degrees of performance in key network factors. For example, while power consumption is a major issue for cellular-based, licensed LPWANs; Quality-of-Service and scalability are main considerations when adopting unlicensed technologies. Standardization is another important factor to think of if you want to ensure reliability, security, and interoperability in the long run.

Learn more about the key considerations for this family of wireless IoT technologies here

[bctt tweet=”Selecting the best wireless technology for your IoT use case, requires an accurate assessment of bandwidth, QoS, security, power consumption and network management.”]

2. Cellular (3G/4G/5G)

Well-established in the consumer mobile market, cellular networks offer reliable broadband communication supporting various voice calls and video streaming applications. On the downside, they impose very high operational costs and power requirements.

While cellular networks are not viable for the majority of IoT applications powered by battery-operated sensor networks, they fit well in specific use cases such as connected cars or fleet management in transportation and logistics. For example, in-car infotainment, traffic routing, advanced driver assistance systems (ADAS) alongside fleet telematics and tracking services can all rely on the ubiquitous and high bandwidth cellular connectivity.

Cellular next-gen 5G with high-speed mobility support and ultra-low latency is positioned to be the future of autonomous vehicles and augmented reality. 5G is also expected to enable real-time video surveillance for public safety, real-time mobile delivery of medical data sets for connected health, and several time-sensitive industrial automation applications in the future.

Also recommended for you: IoT Connectivity – 4 Latest Standards That Will Shape 2020 and Beyond

3. Zigbee and Other Mesh Protocols

Zigbee is a short-range, low-power, wireless standard (IEEE 802.15.4), commonly deployed in mesh topology to extend coverage by relaying sensor data over multiple sensor nodes. Compared to LPWAN, Zigbee provides higher data rates, but at the same time, much less power-efficiency due to mesh configuration.

Because of their physical short-range (< 100m), Zigbee and similar mesh protocols (e.g. Z-Wave, Thread etc.) are best-suited for medium-range IoT applications with an even distribution of nodes in close proximity. Typically, Zigbee is a perfect complement to Wi-Fi for various home automation use cases like smart lighting, HVAC controls, security and energy management, etc. – leveraging home sensor networks.

Until the emergence of LPWAN, mesh networks have also been implemented in industrial contexts, supporting several remote monitoring solutions. Nevertheless, they are far from ideal for many industrial facilities that are geographically dispersed, and their theoretical scalability is often inhibited by increasingly complex network setup and management.

4. Bluetooth and BLE

Defined in the category of Wireless Personal Area Networks, Bluetooth is a short-range communication technology well-positioned in the consumer marketplace. Bluetooth Classic was originally intended for point-to-point or point-to-multipoint (up to seven slave nodes) data exchange among consumer devices. Optimized for power consumption, Bluetooth Low-Energy was later introduced to address small-scale Consumer IoT applications.

BLE-enabled devices are mostly used in conjunction with electronic devices, typically smartphones that serve as a hub for transferring data to the cloud. Nowadays, BLE is widely integrated into fitness and medical wearables (e.g. smartwatches, glucose meters, pulse oximeters, etc.) as well as Smart Home devices (e.g. door locks) – whereby data is conveniently communicated to and visualized on smartphones.

The release of Bluetooth Mesh specification in 2017 aims to enable a more scalable deployment of BLE devices, particularly in retail contexts. Providing versatile indoor localization features, BLE beacon networks have been used to unlock new service innovations like in-store navigation, personalized promotions, and content delivery.

5. Wi-Fi 

There is virtually no need to explain Wi-Fi, given its critical role in providing high-throughput data transfer for both enterprise and home environments. However, in the IoT space, its major limitations in coverage, scalability and power consumption make the technology much less prevalent.

Imposing high energy requirements, Wi-Fi is often not a feasible solution for large networks of battery-operated IoT sensors, especially in industrial IoT and smart building scenarios. Instead, it more pertains to connecting devices that can be conveniently connected to a power outlet like smart home gadgets and appliances, digital signages or security cameras.

Wi-Fi 6 – the newest Wi-Fi generation – brings in greatly enhanced network bandwidth (i.e. <9.6 Gbps) to improve data throughput per user in congested environments. With this, the standard is poised to level up public Wi-Fi infrastructure and transform customer experience with new digital mobile services in retail and mass entertainment sectors. Also, in-car networks for infotainment and on-board diagnostics are expected to be the most game-changing use case for Wi-Fi 6. Yet, the development will likely take some more time.

6. RFID

Radio Frequency Identification (RFID) uses radio waves to transmit small amounts of data from an RFID tag to a reader within a very short distance. Till now, the technology has facilitated a major revolution in retail and logistics.

By attaching an RFID tag to all sorts of products and equipment, businesses can track their inventory and assets in real-time – allowing for better stock and production planning as well as optimized supply chain management. Alongside increasing IoT adoption, RFID continues to be entrenched in the retail sector, enabling new IoT applications like smart shelves, self-checkout, and smart mirrors.

IoT Wireless Technologies

To quickly sum up, each IoT vertical and application has its own unique set of network requirements. Choosing the best wireless technology for your IoT use case means accurately weighing criteria in terms of range, bandwidth, QoS, security, power consumption, and network management.

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