IoT in Renewable Energy: 4 Ways to Optimize A Solar Farm

IoT in Renewable Energy

BehrTech Blog

IoT in Renewable Energy: 4 Ways to Optimize A Solar Farm

Amid growing environmental issues, the energy sector is undergoing significant transformation with a rapid transition towards sustainable power resources. According to the Guardian, global supplies of renewable electricity could increase by 50% in just five years. Unsurprisingly, a surge in the low-cost solar energy is predicted to be the key driver of this growth. As a vast, clean and inexhaustible alternative to fossil fuels, solar power will be an integral part of our future energy grids. With the scale of solar farms quickly ramping up, energy companies need a new approach to managing their assets and ensuring a smooth integration of renewables into the grid. Expanding applications of IoT in the power sector could be a powerful force in this journey.

Challenges of Utility-Scale Solar Farms

Installing and running a utility-scale solar farm is a huge project. While regarded as a relatively mature technology, photovoltaic (PV) solar energy still comes with high unpredictability. Any changes in weather conditions like solar radiation and ambient temperature could cause fluctuations and instability in power outputs. This increases pressure on the grid to maintain consistent electricity supply. As such, continuous environmental monitoring at solar farms is vital to ensure an accurate forecast of power generation rates and respective adjustments in the grid.

Dependence on external conditions isn’t the only hurdle of large-scale solar operations. To optimize the overall efficiency of a solar farm, each panel must operate at peak capacity. Measuring total power outputs of the farm isn’t an issue. However, recording what’s happening at individual modules has been challenging, especially with hundreds or even thousands of on-field PV panels. Wired sensors are common among existing monitoring systems, but the high hardware and installation costs limit a scalable deployment. Therefore, even if inefficiencies are pinpointed on a network level, it’s difficult for operators to trace their root causes. The lack of visibility also causes maintenance to be done either too late or too frequently.

Optimize Solar Farm Operations with IoT in Renewable Energy

Today, IoT technologies have made a breakthrough in remote monitoring to help energy companies better manage their solar power production. Reduced sensor costs and the emergence of innovative connectivity now enable simple and affordable deployment of granular monitoring networks at large-scale solar farms. With such a network, operators can collect critical external and production parameters panel-by-panel and easily access this data from a central user interface. This opens compelling possibilities to improve the efficiency and reliability of solar energy systems.

1. Improved Asset Performance

By combining different data like solar radiation, temperature, wind speed, dust levels and energy outputs of individual panels, grid managers can uncover low-performing units and potential causes. This helps optimize reparation and maintenance planning to enhance asset performance. For example, reduced energy outputs combined with high particle levels in the air could indicate panel soiling and suggest more regular cleaning schedules. Likewise, low efficiencies of individual modules could reveal insulation, configuration and alignment issues.

2. Enhanced Worker’s Productivity

With the granular visibility, technicians can instantly locate and troubleshoot error sources, instead of wasting time inspecting every single panel. What’s more, automated data collection reduces field trips to only maintenance and reparation purposes, freeing up technicians’ time for more important tasks.

3. Effective Production Forecast

Beyond reactive response, the benefits of IoT for renewable energy also include better production forecasts and improved grid stability. With enough historical data at hand, energy companies can apply analytical and predictive models to calculate power generation rates under given weather conditions. As such, they can anticipate how much solar energy can be produced on a certain day, and how other energy resource inputs should be adjusted for demand-supply balance in the grid.

4. Theft and Vandalism Prevention

An IoT-based monitoring system is also a powerful tool to help protect solar panels against theft and vandalism attempts, especially in rural areas. For example, IoT sensors can detect suspicious movements around a panel or if it is dismantled from the supporting structure. An alarm can then be automatically triggered for operators to timely intervene.

Low Power Wide Area Networks (LPWAN) for IoT in Energy

While there are a plethora of wireless standards and protocols today, not all are designed to support granular IoT monitoring systems. You want a solution that is reliable, scalable, but also cost-effective to support the vast number of end points on a utility-scale solar farm. To ensure easy setup and maintenance, devices should be able to operate on independent batteries for years. At the same time, the whole network must allow for straightforward integration into your existing IT environment.

Low Power Wide Area Networks (LPWAN) have established their stand in the smart metering sphere, but their largest potential lies in remote monitoring scenarios. And, the solar sector certainly has its share in this. By providing the packet size and data rates that are aligned with telemetry use cases, LPWANs bring distinct advantages in terms of range, power and costs. With a robust and scalable technology, you can stay on top of your solar systems and seamlessly connect new assets as your business grows. Also, a private, software-driven LPWAN architecture can help you keep data privacy and ownership issues at bay.

Find out more: What is LPWAN?

The potential of IoT in renewable energy is boundless, particularly with the rise of solar energy. Leveraging innovative connectivity like LPWAN, the future smart grid could be fueled with critical data on energy supply for effective load balancing and demand responses. What’s more, grid managers can attain full visibility into energy production on a unit level and understand how individual assets are performing. This altogether facilitates a smooth transition towards a sustainable, renewable-driven energy grid.

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MYTHINGS Smart Sensor: 10 Powerful IoT Applications

smart sensor

BehrTech Blog

MYTHINGS Smart Sensor: 10 Powerful IoT Applications

This week, we announced the release of the MYTHINGS Smart Sensor, a demo platform to demonstrate MYTHINGS’s long-range, robust and power-efficient IoT communication. The MYTHINGS Smart Sensor is not just a powerful pilot test tool; with our reference design offering, it is also available for mass production and full-scale IoT deployments.

The MYTHINGS Smart Sensor is a self-contained, battery-powered unit with multi-sensing capabilities including accelerometer, temperature, humidity, pressure and GPS sensors. But, its most intriguing feature is that you can tailor these sensing functions to your specific needs. Depending on your use case, any of the sensing units can be switched off accordingly to drastically reduce power consumption and improve battery life. On top of that, the sensor also provides the option to collect custom payload through an open serial interface, delivering great deployment flexibility.

The Smart Sensor can be either affixed to an existing object or system to collect condition data (e.g. machine vibration and temperature, asset movement etc.) or installed as a stand-alone unit to collect your preferred ambient data. There are numerous scenarios where the sensor will prove to be a valuable part of your IIoT initiative and help you to improve processes and asset utilization, reduce costs and enhance safety. Here are 10 powerful IoT applications that can be enabled by the MYTHINGS Smart Sensor.

1. Indoor Climate Regulation

Thermal and humidity comfort is a major contributor to employee productivity at both commercial and industrial workplaces. The problem is, while temperature and humidity distribution are uneven across a large building, heating and cooling settings are often uniform and do not reflect actual indoor conditions. This could lead to occupancy discomfort and excessive HVAC use and energy waste. With the MYTHINGS Smart Sensor, you can capture real-time room temperature and humidity readings on a micro-zone level to accurately regulate the HVAC system within a large facility. Constant indoor climate monitoring also helps detect bottlenecks like a malfunctioning furnace or air conditioner at distinct building zones.

2. Machine Health Monitoring

Machine vibration can reveal a lot about its current health status and issues such as misalignments or loose parts. Using the accelerometer in the MYTHINGS Smart Sensor, you can constantly monitor vibration patterns of critical equipment to identify potential damage and execute maintenance in good time. Another way you can use the Smart Sensor to ensure machine health is by keeping air moisture in check. High humidity can cause condensation and corrosion in equipment, while overly an arid atmosphere can lead to frictions in electronic components. Monitoring and maintaining the room humidity within the industry-suggested range of 35% and 65% can help keep these problems at bay.

3. Optimization of Production Processes

Environmental conditions have a significant impact on industrial. For example, in auto manufacturing, fluctuating temperatures can cause inconsistent fluid injection or impact the quality of 3D printed components by accelerating the cooling phase. Continuously measuring ambient temperature and humidity on the shop floor helps circumvent unwanted environmental changes that potentially disrupt your production. Combining machine vibration and ambient data with recorded process parameters further unveil hidden inefficiencies that lower production output.

4. Cold Chain Monitoring

Beyond the production stage, many perishable products in industries like pharmaceutical and food and beverage, require a strictly controlled storage condition. By installing the MYTHINGS Smart Sensor in your storage facility, you can ensure the relative temperature and humidity are within the ideal range to avoid property distortion and optimize product lifetime. Continuous observation of the thermal trend also enables you to quickly pinpoint and act on issues such as, a door unintentionally left open or a cooling equipment failure.

5. Off-Road Fleet Management

Management of vehicles distributed over a large industrial premise can be a great challenge. Older fleets often come with limited, if no telematics ability at all. In this context, MYTHINGS Smart Sensors provide you a versatile option to IoT-enable your fleet without a costly overhaul. Simply attach the sensor on your vehicle and collect its vibration/acceleration data for analysis of moving, idling and engine-off time. With this visibility, you can uncover fuel waste sources due to excessive idling, or detect unauthorized vehicle uses outside the operational time. Having information on actual vehicle utilization at hand, you can also make strategic, informed decisions on the fleet size and composition.

6. Temperature Control in Data Centers

At a data center, excessive heat released from servers can shorten their lifetime by overloading inner fans, increasing energy use and even imposing fire risk. Due to the dynamic heat emission, measuring the overall temperature is less of a concern, but more importantly identifying specific hot spots within the server room. Low-power MYTHINGS Smart Sensors enable you to collect granular, rack-by-rack temperature data to create an accurate data center heat map for effective control measures.

7. Asset Tracking

Knowing where your assets allows you to streamline operations and improve productivity. With its GPS function, the MYTHINGS Smart Sensor can collect position data of any distributed asset on your industrial campus. In indoor environments, GPS signals can be unstable. Here, air pressure and accelerometer readings can help determine vertical and horizontal movements to a certain extent. This enables dead reckoning calculations from knowing the last GPS location.

8. Anti-Theft Protection

The accelerometer in the MYTHINGS Smart Sensor can also be a great instrument for anti-theft protection. For example, it can inform you if an important asset that should be stationed is moved. Just install the sensor on your critical asset and get notified when a suspicious movement is detected.

9. Intrusion Detection

Besides theft detection, the Smart Sensor can be part of your IoT-enabled security system to detect intrusion at night, outside operational hours or in areas with restricted access. By affixing the sensor to the outer edge of a door, acceleration of the door can be measured when it opens. Having an emergency workflow set up, an alarm can be then triggered to inform you of the potential intrusion.

10. Electrical Fire Safety

Electrical failures are the leading cause of fire incidents across commercial and industrial facilities. While useful in detecting overheating caused by circuit issues, infrared inspections of electrical panels and cabinets are typically done on an annual basis. This leaves power systems unattended for most of the time. With a Smart Sensor permanently fixed to the electrical enclosure; you can keep an eye on thermal changes in your distributed power system round-the-clock. Elevated temperatures can quickly be diagnosed for counteraction to prevent fire hazards.


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9 Interesting Wireless IoT Sensor Types and Their Applications

Wireless IoT Sensor

BehrTech Blog

9 Interesting Wireless IoT Sensor Types and Their Applications

Wireless sensors are the backbone of IoT and its industrial counterpart the Industrial Internet of Things (IIoT). In a previous blog post, we talked about some of the more popular sensor types such as temperature, pressure, and accelerometers. In this blog, we discuss a few more interesting wireless IoT sensor types on the market.

Wet Bulb Temperature

Whereas standard, or dry bulb temperature sensors do not take moisture in the air into account when reporting the temperature, wet-bulb temperature sensors provide measurements closer to the true (thermodynamic) temperature. A wet-bulb sensor is essentially a thermometer covered in a water-soaked fabric over which air is passed. In drier, less humid air, the water on the cloth evaporates more quickly, whereas in more humid conditions, the moisture in the air causes the water in the cloth to evaporate more slowly.

When used in conjunction with a dry bulb sensor, a wet bulb temperature sensor can calculate measurements such as relative humidity (difference between the two sensors) and dew point (the temperature at which water starts to condense and form droplets). These measurements are useful in number of applications for humidity control to help avoid condensation within a building which can lead to discoloration, mode/mildew growth and structural damage.

Enhanced Voice Recognition using Facial Vibrations

Voice recognition and applications that use it are everywhere, from virtual assistants to our phones, tablets, and automobiles. However, the voice recognition capabilities in these systems are not always reliable, as they might not understand our voices clearly enough in the presence of ambient or environmental noise.

A new hardware approach is being used to improve voice recognition. This technology uses a laser-based sensor to measure tiny vibrations in a person’s throat and face when they speak. The laser greatly augments the system’s accompanying microphone signal by filtering out background noises and providing an isolated near-perfect signal.

There are many use cases for this technology including, voice recognition in automotive, virtual reality, aviation, industrial handsets and wearables.

Structural Health Monitoring Sensors

Structural Health Monitoring (SHM) refers to the use of sensors for collecting and analyzing data, over the service life of structures such as bridges. Instead of reacting to damage that is already occurring, SHM is more about proactive maintenance through the continuous assessment of the structural integrity in bridges and other structures. For example, bridge design must consider factors such as vibration, wind, weather, and traffic alongside the damage that they can cause. Without SHM sensors, inspectors must rely on visual inspection.

There are many types of wireless IoT sensors used in Structure Health Monitoring. Accelerometers can help identify vibration-based damage, while anemometers on suspension bridges monitor wind speed and direction that potentially impact their integrity.

Ultraviolet Radiation Detection

Exposure to radiation can be deadly. When the exposure is high enough, it can remove an electron from an atom. If it reaches human skin cells, the risk of DNA damage and skin cancer is significant. People working with or around radioactive substances wear a device known as a dosimeter. Dosimeters contain phosphor crystals that are designed to trap electrons freed by harmful ionizing radiation.

When heated, the crystals release trapped electrons in the form of light. These electrons can be measured to determine the amount of radiation its wearer has been exposed to. On the consumer side, ultra-violet (UV) detection wearables, apps and stickers have recently been developed to monitor and prevent dangerous levels of sun exposure, and many of these devices use dosimeters.

Air Pollution Sensors

Air pollution is a major problem in cities around the world. While air pollution detection is usually handled by governmental agencies, advances in technology are allowing individuals and community groups to monitor and detect air pollution around their homes, schools, and parks. Two types of air pollution sensors are particulate matter sensors and gas phase sensors.

Particulate matter sensors can detect particulates using either optical particle counting or volume scattering. In the former, particles entering the sensor are individually sized and counted based on how they scatter light. In the latter, particles enter the sensor scatter light from an internal light source.

Gas phase sensors detect gasses such as nitrogen oxide and ozone using a number of different techniques. Ozone and nitrogen dioxide detectors use electrochemical cells to detect gasses as they pass through air or using a metal oxide semiconductor.

Snow Level Monitoring

Another interesting wireless IoT sensor use case is the monitoring of snow levels in real time. Snow-related sensors can help skiers determine the quality of ski tracks and can even help with avalanche prevention.

Snow depth can be measured using a variety of methods including ultrasonic and/or laser sensing. In the case of ultrasonic sensors, the sensor is placed at a point where the snow level is to be measured. This sensor continuously captures data on the snow depth and sends it to the microcontroller.

Identification of Storage Incompatibilities

In today’s global economy, goods are continually transported between continents using sea containers. Accidents with and mismanagement of these containers can cause significant problems to the parties involved in the transaction as well as the environment. One method of preventing problems is to use wireless IoT sensors to monitor the logistics of such operations.

Sensors within one container exchange information with other pallets or containers stored around it, using RFID and similar technologies. For example, if a pallet of dangerous goods is located next to a pallet with flammable materials, warning messages can be sent. This allows corrective measures to be taken before a problem occurs.

Water Quality

Poor water and sanitation conditions contribute to illness and millions of deaths worldwide. Conventional water monitoring processes are manual, time-consuming and do not provide real-time results. Wireless IoT sensor nodes offer a promising alternative as they can detect parameters related to water quality such as pH, electrical conductivity, oxidation reduction and turbidity. Like other use cases, real-time water quality monitoring enables early warning abilities and timely response in the event of water contamination.

Solar Radiation

Radiation from the sun is received as wavelengths known as the solar spectrum. A pyranometer is a type of sensor that converts received solar radiation into an electrical signal that can be measured.

There are several use cases / applications that use solar radiation measurements including:

  • Measuring the efficiency of solar panels in converting the sun’s energy into electricity.
  • Determining when solar panels need to be cleaned.
  • Golf and park maintenance including the scheduling of irrigation.
  • Weather prediction models in meteorology.

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Costs of Occupational Injuries and Illnesses

Costs of Occupational Injuries and Illnesses

BehrTech Blog

14 Eye-Opening Facts About Worker Safety

The costs of occupational injuries and illnesses is a major pain point common across a variety of industries. Industrial work is traditionally difficult and dangerous; and has been identified by the International Labour Organization as a primary focus for improving workplace safety and wellness globally.

With millions of workers affected by occupational health and safety incidents annually and a growing focus on improving workplace conditions and safeguards, having an understanding of the true costs of occupational injuries and illnesses is essential.

The infographic below recaps 14 of the most eye-opening facts about worker safety and the substantial costs that companies bear when employees are injured on the job.

costs of occupational injuries and illnesses

To improve worker safety, innovative IoT and wireless connectivity solutions are being utilized to monitor and report on the health and safety of workers. Intelligent devices such as watches, helmets and vests can now capture vital physical metrics in real-time like heart rate, temperature, movement, activity, and location. In parallel, environmental sensors can be installed on site to monitor critical information about employees’ working conditions and their exposure to external dangers. With the addition of advanced analytics platforms, notifications can be sent when accidents or potential hazards are detected to help reduce and prevent workplace accidents, injuries and fatalities.  

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Top 10 IoT Sensor Types & How They’re Being Used


BehrTech Blog

Top 10 IoT Sensor Types 


Sensors are everywhere. They’re in our homes and workplaces, our shopping centers and hospitals. They’re embedded in smart phones and an integral part of the Internet of Things (IoT). Sensors have been around for a long time. The first thermostat was introduced in the late 1880s and infrared sensors have been around since the late 1940s. The IoT and its counterpart, the Industrial Internet of Things (IIoT), are bringing sensor usage to a new level.

Broadly speaking, sensors are devices that detect and respond to changes in an environment. Inputs can come from a variety of sources such as light, temperature, motion and pressure. Sensors output valuable information and if they are connected to a network, they can share data with other connected devices and management systems. 

Sensors are crucial to the operation of many of today’s businesses. They can warn you of potential problems before they become big problems, allowing businesses to perform predictive maintenance and avoid costly downtime. The data from sensors can also be analyzed for trends allowing business owners to gain insight into crucial trends and make informed evidence-based decisions.

Sensors come in many shapes and sizes. Some are purpose-built containing many built-in individual sensors, allowing you to monitor and measure many sources of data. In brownfield environments, it’s key for sensors to include digital and analog inputs so that they can read data from legacy sensors.

There are many types of IoT sensors and an even greater number of applications and use cases. Here are 10 of the more popular types of IoT sensors and some of their use cases.

[bctt tweet=”IoT sensors have become critical to improving operational efficiency, reducing costs and enhancing worker safety.”]
IoT-Sensor - Temperature

1. Temperature Sensors

Temperature sensors measure the amount of heat energy in a source, allowing them to detect temperature changes and convert these changes to data. Machinery used in manufacturing often requires environmental and device temperatures to be at specific levels. Similarly, within agriculture, soil temperature is a key factor for crop growth.

IoT Sensor - Humidity

2. Humidity Sensors

These types of sensors measure the amount of water vapor in the atmosphere of air or other gases. Humidity sensors are commonly found in heating, vents and air conditioning (HVAC) systems in both industrial and residential domains. They can be found in many other areas including hospitals, and meteorology stations to report and predict weather.

IoT Sensor Pressure

3. Pressure Sensors

A pressure sensor senses changes in gases and liquids. When the pressure changes, the sensor detects these changes, and communicates them to connected systems. Common use cases include leak testing which can be a result of decay. Pressure sensors are also useful in the manufacturing of water systems as it is easy to detect fluctuations or drops in pressure.

IoT Sensor Proximity

4. Proximity Sensors

Proximity sensors are used for non-contact detection of objects near the sensor. These types of sensors often emit electromagnetic fields or beams of radiation such as infrared. Proximity sensors have some interesting use cases. In retail, a proximity sensor can detect the motion between a customer and a product in which he or she is interested. The user can be notified of any discounts or special offers of products located near the sensor. Proximity sensors are also used in the parking lots of malls, stadiums and airports to indicate parking availability. They can also be used on the assembly lines of chemical, food and many other types of industries.

IoT Sensor Level

5. Level Sensors

Level sensors are used to detect the level of substances including liquids, powders and granular materials. Many industries including oil manufacturing, water treatment and beverage and food manufacturing factories use level sensors. Waste management systems provide a common use case as level sensors can detect the level of waste in a garbage can or dumpster.

IoT Sensor Accelerometer

6. Accelerometers

Accelerometers detect an object’s acceleration i.e. the rate of change of the object’s velocity with respect to time. Accelerometers can also detect changes to gravity. Use cases for accelerometers include smart pedometers and monitoring driving fleets. They can also be used as anti-theft protection alerting the system if an object that should be stationary is moved.

IoT Sensor Gyroscope

7. Gyroscope

Gyroscope sensors measure the angular rate or velocity, often defined as a measurement of speed and rotation around an axis. Use cases include automotive, such as car navigation and electronic stability control (anti-skid) systems. Additional use cases include motion sensing for video games, and camera-shake detection systems.

IoT Sensor Gas

8. Gas Sensors

These types of sensors monitor and detect changes in air quality, including the presence of toxic, combustible or hazardous gasses. Industries using gas sensors include mining, oil and gas, chemical research andmanufacturing. A common consumer use case is the familiar carbon dioxide detectors used in many homes.

IoT Sensor Infrared

9. Infrared Sensors

These types of sensors sense characteristics in their surroundings by either emitting or detecting infrared radiation. They can also measure the heat emitted by objects. Infrared sensors are used in a variety of different IoT projects including healthcare as they simplify the monitoring of blood flow and blood pressure. Televisions use infrared sensors to interpret the signals sent from a remote control. Another interesting application is that of art historians using infrared sensors to see hidden layers in paintings to help determine whether a work of art is original or fake or has been altered by a restoration process.

IoT Sensor Optical

10. Optical Sensors

Optical sensors convert rays of light into electrical signals. There are many applications and use cases for optical sensors. In the auto industry, vehicles use optical sensors to recognize signs, obstacles, and other things that a driver would notice when driving or parking. Optical sensors play a big role in the development of driverless cars. Optical sensors are very common in smart phones. For example, ambient light sensors can extend battery life. Optical sensors are also used in the biomedical field including breath analysis and heart-rate monitors.

Industrial Wireless Sensor - MYTHINGS Smart Sensor


The MYTHINGS Smart Sensor is a self-contained, battery-powered multi-purpose IoT sensor that allows you to capture critical data points like acceleration, temperature, humidity, pressure and GPS. The smart sensor is integrated with the MYTHINGS Library – a hardware independent, small-footprint and power-optimized library of code, featuring the MIOTY (TS-UNB) low-power wide area network protocol. Learn more.


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5 Industrial IoT (IIoT) Predictions for 2019

IIoT Predictions for 2019

BehrTech Blog

5 IIoT Predictions for 2019


We are in the midst of digital transformation and the industry 4.0 revolution. From manufacturing and mining to oil and gas and utilities, more companies are adopting the Internet of Things for its obvious business benefits. Accenture estimates the Industrial Internet of Things (IIoT) could add $14.2 trillion to the global economy by 2030.

Industrial IoT solutions continue to prove their immense value; allowing for an easier, and more efficient and affordable way to manage processes.

As the Industrial IoT landscape rapidly evolves, what can we expect in the coming year? Here are our 5 IIoT predictions for 2019.

[bctt tweet=”Embracing upcoming IIoT trends as part of your next digital strategy is key to driving continuous innovation and staying above the competition.”]

1. LPWAN Helps Break Down Industrial Data Silos

Legacy industrial systems often run on disparate, proprietary communication networks that don’t enable data exchange. In addition, many industrial campuses are located in remote areas with extremely difficult terrains and topography, alongside heavy physical obstructions. This makes traditional wired and wireless solutions like cellular or short-range technologies too complex, expensive and unreliable to implement; leaving industrial companies with huge amounts of isolated and inaccessible data acquisition points.

Predicted to support 3 billion IoT connections by 2025, Low-Power Wide Area Networks (LPWANs) are a new wireless phenomenon promising to combat these brownfield challenges. With its long range, deep penetration, and ultra-low power consumption, LPWAN brings reliable connectivity to previously infeasible industrial locations. As a cost-effective, easy to deploy and manage solution, these networks can be retrofitted in large-scale brownfield facilities to IoT-enable legacy asset and systems.

“Wireless connectivity that was previously too expensive to implement or not technically feasible to be deployed is now possible,” emphasizes Michel Hepp, BehrTech’s VP of Global Sales. “We now have viable communications solutions that can connect these previous ‘islands of data’ to the enterprise.”

There are numerous technologies that currently fall under the LPWAN umbrella. To seamlessly support ever-growing data traffic in 2019, a robust and scalable solution with strong interference immunity will be the focus.

2. Interoperability Gives Rise to Turnkey IoT Solutions

Interoperability of Industrial IoT devices will be critical for the progress of IIoT ecosystems. McKinsey & Company predicted that IoT interoperability is required to create 40 percent of the potential value of the Internet of Things.

IoT interoperability is the ability for systems or elements of systems to interact and harmoniously function with each other, regardless of their manufacturer or technical specifications. For example, a communication protocol should be compatible with any commercial, off-the-shelf hardware like transceivers and gateways. It should also be able to interface and exchange data with cross-vendor cloud platforms for data storage and analytics.

IoT is inherently an ecosystem game where no single technology alone can provide a complete solution. Interoperability, fueled by open, industry-standard technologies, will enable a new wave of turnkey solutions delivered by IoT vendors and system integrators. By bringing different components of the IoT value chain together, these out-of-the-box offerings help customers streamline complexity and accelerate ROIs.

As BehrTech’s Chief Product Officer, Wolfgang Thieme highlights, “since IoT involves so many technologies from the sensor through the network to the cloud, there is a critical need for end-to-end solutions. It is difficult for end customers to adopt and integrate everything themselves. Therefore, a strong partner ecosystem is key for successful IoT connectivity and solutions.”

3. End-to-End Communications Security Becomes A Norm

Reducing security vulnerabilities will remain a primary focus. With the rising number of IoT devices, hackers and cybercriminals are continuously finding new ways to compromise IoT devices and networks.

In the 2019 fight against cybercrime, multi-layered, end-to-end security throughout the IoT data chain – from end nodes to the gateway to the Internet and finally end users’ application platforms – will be imperative. Advanced Encryption Standard (AES) can be paired with Transport Layer Security (TLS) protocol to enable such a versatile end-to-end security. AES is an open encryption standard widely employed for data link layer encryption in low-power IoT networks, while TLS is an application-layer cryptographic protocol for secure web communications. Adoption of these industry-standard, well-proven solutions is crucial to protect the integrity and confidentiality of IoT data against imminent cyber-threats.

What’s more, securing IoT devices will become more complex due to the diversity of control platforms. To overcome such complexity, Microsoft released a list of security best-practices for IoT devices:

Hardware-Based Root of Trust: To make IoT devices hardware-secure against attackers a single-purpose hardware should be used as well as built-in features to detect a hardware attack.

Small Trusted Computing Base: By only using a small trusting computing base and minimizing the hardware and software, failures will be reduced.

Defense in Depth: When using multiple security layers, the device will still be secure even when an attacker manages to remove one layer because other measures can still prevent intrusion.

Compartmentalization: By separating hardware and software an attacker doesn’t automatically gain access to all other parts of the device when he has hacked one of them.

Certificate-Based Authentication: Certificate-based authentication is recommended since it can’t be forged like a password-base authentication.

Renewable Security: Renewing the security with regular updates will help to approach new threats and vulnerabilities.

Failure Reporting: With built-in and automated failure reporting, attempted attacks can be analyzed and used to improve security.

4. Edge Computing Goes Mainstream

According to TechRepublic, by 2020, data traffic generated by smart sensors and other IoT devices will reach 507.5 zettabyte. Managing and analyzing this huge amount of data will be a significant challenge for organizations as cloud computing remains under pressure to meet the data computing and intelligent service demands of IoT devices and applications.

That is why edge computing is gaining more popularity. Instead of data management and analysis being performed at big cloud and enterprise data centres, it is generated, collected and analyzed close to the data source i.e. IoT sensors and devices. This reduces the latency between devices and the data processing layer to allow data to be delivered in real-time. Edge computing also enhances compliance and security as data is stored locally, giving hackers fewer opportunities to access all data at once.

As IoT deployments expand in 2019, more companies will look to build infrastructures that can handle this massive amount of critical data. Edge computing provides the reliability and security needed to make intelligent decisions in real-time.

5. Digital Twin Advances Operational Excellence

Another innovation expected to revolutionize Industrial IoT are Digital Twins.

A Digital Twin is a near real-time virtual representation of a physical object or process built to optimize business performance. By creating a complete digital footprint of critical assets, the digital twin enables industries to detect physical issues more quickly, predict outcomes more accurately, and design and build better products, systems, and processes.

For example, manufacturers can use digital twins to create a virtual representation of a field asset. Then as data is captured from smart sensors embedded in the asset it provides visibility into real-world performance and operating conditions. Manufacturers can also simulate that real-world environment for predictive maintenance.

McKinsey predicts linking the physical and digital worlds could generate 11.1 trillion a year in economic value by 2025, while Gartner predicts that roughly half of all large industrial companies will be using digital twins by 2021. As more industries focus on reducing operating costs and extending the life of equipment, we will certainly see a spike in Digital Twin applications and uses cases in 2019.

Today, digital transformation is no more a choice, but a must for industrial companies to secure their competitive edge. Beyond the hype, IIoT is getting closer to reality with increasing maturity and adoption of sensor, networking and analytics technologies. Embracing upcoming IIoT trends as part of your next digital strategy is key to driving continuous innovation process and stay on top of the competition in 2019.


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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


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


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.


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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Learn More about Next-gen IoT Wireless Technologies

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