Introduction

Over the past few decades, the number of objects (things) connected to the internet has grown exponentially. And with the everyday development of technology, the Internet of things (IoT) has penetrated in almost every application area. It has revolutionized the way machines interact and provided cutting-edge solutions to a variety of real-life problems.

As the IoT in itself is a large hood, covering almost every sphere of technology nowadays, we will be focussing  our discussion on Narrow Band Internet of Things (NB-IoT) in this article.  We will be exploring  NB-IoT and how it is impacting the volume of connected devices and IoT connectivity infrastructure.

What all we have already?

In order to connect sparsely deployed IoT devices, the present short range communication technologies like BLE, ZigBee, WiFi are not a viable solution. To get over this limitation, several Wide Area Network (WAN) technologies have been evolved such as LoRaWAN (Long Range WAN), SigFox, LTE-CatM and NB-IoT. Since these technologies are meant for low powered battery operated devices, we name them as Low Power Wide Area Network (LPWAN) technologies. The four key features of LPWAN technologies are Long range, low power consumption, low throughput  and low cost. As there are many LPWAN technologies, it’s very interesting to see how NB-IoT stands out.

LPWAN provides voice to objects by enabling them to communicate. Consider a dustbin which is full and needs to be emptied. Using LPWAN technology, a dustbin can send a message to the user, “I am full, please empty me”, which in turn can ensure timely garbage clearance and avoid periodic manual checks on the other hand.

Where does the problem lie?

Existing cellular infrastructure and internet connectivity is designed keeping the humans at the centre point to fulfil their different data requirements. IoT devices are very small in size and are nascent in the world of human centric data infrastructure and therefore, connecting them directly to the existing  internet infrastructure is not feasible.

Traditional cellular standards are not scalable for IoT because they were built with focus on either voice or bandwidth intensive low-latency data applications. And there are other reasons for it, like coverage, device density, cost and power. Gap between short range technologies such as Bluetooth/Zigbee/Wi-Fi and cellular technologies like 3G/4G is filled by NB-IoT. As short range technologies require a gateway to transfer data collected over the internet, NB-IoT has an edge over them by enabling direct internet access to end devices. NB-IoT  reduces complexity, caps maximum data rates and limits bandwidth.

Licensed vs Unlicensed LPWAN

As most LPWAN technologies are wireless in nature, they consist of several radio frequency bands. Based on the frequency band allocation LPWAN can be categorized into licensed and unlicensed band technologies.

Licensed band LPWAN technologies use authorised frequencies allocated by a regulatory authority of a country to the cellular service providers. Therefore they are not free to use but are backed by widespread cellular networks which can be used on subscription basis. Use of dedicated frequency spectrum overcomes drawbacks of unlicensed band LPWAN. Licensed band LPWAN technologies are supported and standardized by  3^rd Generation Partnership Project (3GPP). It is basically an organisation behind the standardization of cellular systems. It includes technologies like GSM/GPRS, LTE-M and NB-IoT.

Whereas, unlicensed band LPWAN technologies are non 3GPP standards like SigFox, LoRaWAN etc. They use ISM (Industrial, Scientific and Medical) band frequencies which are openly available and free to use for anybody. Due to this fact they are often subjected to security, reliability, overcrowding and interference issues.

NB-IoT vs Other Technologies

NB-IoT has faster response time than LoRa and guarantees better quality of service (QoS) which means that chances to send the message to the intended recipient are much higher as compared to unlicensed band LPWAN technologies. Also licensed LPWAN technologies like NB-IoT offer higher throughput and longer range communication as compared to unlicensed band LPWAN technologies (LoRa, SigFox).

Both LTE-M and NB-IoT are optimised for the requirements of different IoT applications such as smart metering, precision agriculture. residential security etc. But there are certain differences between these two licensed band technologies. NB-IoT offers low bandwidth data rate connections at low cost while LTE-M is optimised for higher data rates and mobile connections. NB-IoT is suitable for all those applications where lower bandwidth, less data, improved battery life, improved range is required.

Below table covers the major differences between popular LPWAN technologies :

Here comes the NB-IoT

Narrow Band Internet of Things (NBIoT) is a Low Power Wide Area Network (LPWAN) radio technology developed by 3GPP. The specification was frozen in 3GPP Release 13 (LTE Advanced Pro), in June 2016.

It has been developed to cater the needs of very small, low resourced and battery operated connected devices which require low data rate communication.  This technology enables IoT devices to send their data directly to the cloud network without requiring any gateway for data aggregation.

NB-IoT supports high connection density, wide-area coverage and low power consumption. It is backed by an excellent cellular communication network, which is already widespread. Therefore, NB-IoT stands out as a promising communication technology for connected devices.

As cited by ABI research, “IoT applications that require more frequent communications will be better served by NB-IoT which has no duty cycle limitations operating on the licensed spectrum.”

Salient features of NB-IoT

1. NB-IoT provides enhanced coverage in rural and deep indoor areas. It is good for applications with high device density.
2. NB-IoT has low power consumption. Battery life is more than 10 years for a wide range of use cases. Thus, it improves efficient power consumption, system capacity, and spectrum efficiency.
3. Low latency.
4. High sensitivity.
5. NB-IoT is low-cost technology.
6. NB-IoT offers massive connectivity. It can co-exist with 2G, 3G, and 4G mobile networks.

Physical features of NB-IoT

Some of the physical features of NB-IoT are mentioned in the following table:

NB-IoT deployment

NB-IoT can be deployed in three ways:

1. Independent Deployment (stand-alone mode)
2. Guard Band Deployment (Guard-band mode)
3. In-Band Deployment (In-band mode)

Is it power efficient?

1. Half-Duplex:

As NB-IoT supports half-duplex transmission, only one transceiver is required for both uplink and downlink, unlike LTE which contains two transceivers one for each mode. As it uses a single transmitter, the RF unit consumes less power making it power efficient and eventually resulting in a lower cost.

2. Less Transmission Power:

NB-IoT uses only one antenna, regardless of the regulation for using two antennas, simplifying the implementation as well. By reducing the user equipment calculation capability, the protocol volume is simplified. This simplifies the circuitry, resulting in a more cost-effective chipset.

3. Power saving mode (PSM):

With PSM,  devices can go into deep sleep for upto 12.1 days after the device is registered with the network. Whenever required devices can wake up to track area updates and  send data which allows saving power.

4. Discontinuous Reception (DRX):

With DRX , devices need not to monitor control channels most of the time. In addition, eDRX (extended DRX) has been added in Release 13 of 3GPP standard, which further extends the sleep cycle of the terminal in idle mode and reduces unnecessary cell startup.

Note: Power saving mode (PSM) and Discontinuous Reception (DRX) are introduced by Release 12 for lowering power requirements.

Is it cost effective?

Since SigFox and LoRa are unlicensed  LPWAN technologies, their cost is automatically reduced because of the freely available ISM band. However this is not the case with NB-IoT because it uses a dedicated licensed frequency spectrum thus it becomes important for NB-IoT to keep its cost low in order to survive in the competitive market. When NB-IoT is deployed in in-band mode, the installation cost is lower than that of LoRa.

NB-IoT uses a simplified hardware mechanism which can connect upto 1000 end devices with 1 base station. It uses already existing cellular infrastructure which aids in minimizing the cost of deployment.

As NB-IoT is similar to the legacy LTE, it is very complex to reduce the costs. However, to minimise the cost, it is necessary to trade-off the performance of the system and simplify the protocol implementation.

Applications of NB-IoT

There is a variety of applications for this exciting technology, some of them are mentioned as follows:

1. Smart cities (streetlights, parking, waste management etc.)
2. Land/Agriculture and environment monitoring
3. Pollution monitoring
4. Animal Tracking
5. Smart metering (electricity, water, gas)
6. Facility management services
7. Connected Industrial appliances

Applications where sensors are installed in remote locations, with limited mobility and run on battery to send small amounts of data occasionally are benefitted by NB-IoT Technology.

Some success stories in the field of NB-IoT

Telecom operators are always looking at effective implementation of IoT and IoT related other technologies to transform their business models and to build revenue generation opportunities. During the forecast period from 2022 to 2027, the global IoT market is expected to register a compound annual growth rate (CAGR) of 10.53%. Also, the NB-IoT chipset market is expected to grow to USD 2,484 million by 2025 at a CAGR  of 40.0%.

There are several fueling factors in the growth of NB-IoT chipset market, some of them are:

1. Exponential rise in the use of connected devices.
2. Increasing participation of industry players in the development of NB-IoT.
3. Active participation of startups in IoT and its sub-fields.
4. Widening applications of NB-IoT technology.
5. Growing acceptance of IoT.

Ever increasing demand for wearable devices due to COVID-19 outbreak.

Key market players in the NB-IoT world

There are many industry players in the NB-IoT chipset market, some of them are mentioned below:

1. Huawei (China)
2. Samsung (South Korea)
3. Sequans Communications (France)
4. MediaTek (Taiwan)
5. Nordic Semiconductor (Norway)
6. Altair Semiconductor (Sony Group Company) (Israel)
7. Cheerzing (China)
8. Sercomm (Taiwan)
9. SIMCom (China)
10. Sierra Wireless (Canada)
11. u-blox (Switzerland)
12. ZTE (China)
13. RDA (China)
14. Qualcomm (US)

The market has seen active participation of many start-ups. Riot Micro (Canada) and Commsolid (A Goodix Company) (Germany) are few of the emerging startups in the market.

Key Indian market players

India is one of the largest NB-IoT markets in the world.  There are also many Indian industries that are very interested  in reaping the benefits that NB-IoT offers. Some of the leading Indian companies are as follows:

1. Bharti Airtel
2. Vodafone India
3. Reliance Jio

Drawbacks of NB-IoT

Every coin has two sides, so does NB-IoT. Although NB-IoT presents many advantages that are in line with IoT applications, there are still issues that need to be addressed such as:

1. Some design specifications of NB-IoT makes it hard to send larger amounts of data to the device.
2. It is difficult to implement firmware updates over the air.
3. NB-IoT is suitable for fixed location rather than roaming assets because of network and tower handoff.

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Conclusion

There are several benefits of NB-IoT and many of them we have read above. With the number of increasing connected devices and wide spread opportunities available in different application areas the use of NB-IoT technology will only increase.

Hope you have enjoyed reading and this article has helped you to enhance your knowledge. Do you have any questions or want to add to it please feel free to comment below. We will love to read your comments.

Reference :

Narrowband-IoT Market Size, Share | Global Industry Report, 2019-2025 (grandviewresearch.com)

5G Estimated to Reach 1.5 Billion Subscriptions in 2024 – IoT Business News

3GPP NB-IoT Deployment and Optimization Challenges – VIAVI Perspectives (viavisolutions.com)

Narrowband IoT Market | Global Trends, Size, Share, Analysis 2019- 2027 (inkwoodresearch.com)

Agriculture plays a significant role in the economic sector. Automation in agriculture is the main
concern across the world. The population is increasing tremendously and with this increase the
demand for food and employment is also increasing. The traditional methods which were used by
the farmers were not sufficient enough to fulfil these requirements. Thus, new automated methods
were introduced. IoT provides real time data for algorithms to increase agricultural efficiencies,
improve crops yields and reduce food production costs. It allows them to identify areas that need
irrigation, pesticide or fertilization treatment.

Existing Solutions without IoT are :

The farmers use fertilisers and pesticides on a large scale. They have also brought their land under a
high yielding variety of seeds. They have mechanised agriculture by introducing machines in various
processes of farming. Farmers use various irrigation systems to fulfil the need for water.

Pain Area of the Farmers and Agri-related Things :

The agricultural industry faces various challenges such as lack of effective irrigation systems, weeds,
issues with plant monitoring due to crop height and extreme weather conditions. But the
performance can be increased with the aid of technology and thus these problems can be solved. It
can be improved with different IoT driven techniques like remote sensors for soil moisture content
detection and automated irrigation with the help of GPS.

How IoT Help to Develop Agriculture Domain :

There are some applications of IoT in farming :

Use of weather forecasting: farmers can analyse weather conditions by using weather
forecasting which helps them to plan the type of crop can be grown and and when should seeds be
sown

Soil and crop health monitoring system : Apps which helps farmers to monitor soil and crop health conditions and produce healthy crops with a higher level of productivity.

Analyzing crop health by drones : In this technique, the drone captures data from fields and then data is transferred via a USB drive from the drone to a computer and analyzed by experts. It also helps the farmer to identify pests and bacteria helping farmers to timely use of pest control and other methods to take required action.

AI-enabled system to detect pests : AI systems use satellite images and compare them with historical data using AI algorithms and detect if any insect has landed and which type of insect has landed like the locust, grasshopper, etc. And send alerts to farmers to their smartphones so that farmers can take required precautions and use required pest control thus AI helps farmers to fight
against pests.

Yield mapping : The raw log document contains focuses which are recorded during turns and as
the grain moves through a consolidation is a deferred process, the sensor estimations neglect to
compare to the careful gathering areas.

Precision Farming and Predictive Analysis :

Farmers can make use of IoT to estimate the date to sow crops and allocate the required resources for growing these crops, such as fertilizer and water, etc. to get the maximum results. This technology has the potential to solve one of the biggest problems that humankind has o face.

What is IIoT/Industry 4.0?

Introduction

Industry 4.0 refers to the transformation of industry through the intelligent networking of machines and processes with the help of information and communication technology.
● The term is used interchangeably with the ‘fourth industrial revolution.
● Industry 4.0 comes from the German term ‘Industry 4.0’ It was first used in a project in the high-tech strategy to transform German manufacturing in which the Internet of Things and cyber-physical systems took center stage, along with a further focus on production, people, environment, and security.
● It is the digital transformation of production and related industries and value creation processes. Products and means of production get networked and can communicate, enabling new ways of production, value creation, and real-time optimization.
● Cyber-physical systems create the capabilities needed for smart factories. These are the same capabilities we know from the Industrial Internet of Things like remote monitoring or track and trace.

1. Big data
In Industry 4.0, Big Data is collected from a wide range of sources, from factory equipment and Internet of Things (IoT) devices, to ERP and CRM systems, to weather and traffic apps.

2. Cloud computing
It provides the foundation for most advanced technologies from AI and machine learning to
the Internet of Things and gives businesses the means to innovate.

3. Augmented reality
Augmented reality, which overlays digital content on a real environment, is a core concept of
Industry 4.0. With an AR system, employees use smart glasses or mobile devices to visualize
real-time IoT data, digitized parts, repair or assembly instructions, training content, and more
when looking at a physical thing like a piece of equipment or a product.

4. IOT
The Internet of Things (IoT) is the network of physical objects that contain embedded
technology to communicate and sense or interact with their internal states or the external
environment. Most physical things in Industry 4.0 devices, robots, machinery, equipment,
products use sensors and RFID tags to provide real-time data about their condition,
performance, or location.

5. Additive manufacturing
Additive manufacturing, or 3D printing, is another key technology driving Industry 4.0, 3D
printing was initially used to as a rapid prototyping tool but now offers a broader range of
applications, from mass customization to distributed manufacturing.

6. Autonomous robots
With Industry 4.0, a new generation of autonomous robots is emerging. Programmed to
perform tasks with minimal human intervention, autonomous robots vary greatly in size and
function, from inventory scanning drones to autonomous mobile robots for pick and place
operations. Equipped with cutting edge software, AI, sensors, and machine vision, these
robots are capable of performing difficult and delicate tasks and can recognize, analyze, and
act on information they receive from their surroundings.

7. Simulation
Simulation is the term for developing planning exploratory models to optimize decision
making as well as the design and operations of complex and smart production system.

8. Cybersecurity
With the increased connectivity and use of Big Data in Industry 4.0, effective cybersecurity is
paramount. By implementing a Zero Trust architecture and technologies like machine
learning and blockchain, companies can automate threat detection, prevention, and response –
and minimize the risk of data breaches and production delays across their networks.

Major component of Industry 4.0 :

1. CPS (Cyber physical system:
2. IOT (Internet of things)
3. Cloud computing
4. Cognitive computing

1. CPS (Cyber-physical system)
   Cyber-physical system the term at integrating cyber and physical manufacturing process,
   either in other words computer and network should monitoring the physical manufacturing
   processes at the different level.
2. IOT (Internet of things)
   IOT is the term to enable Machineries & objects like sensor & mobile phones to
   communicate while allowing human to all workout solutions. Such integration makes it easy
   for cyber physical system to work and solve problem at independent level. The internet of
   things is the support system of cyber physical system cooperation with each other via unique
   address scheme.

3. Cloud computing
   Cloud computing is the term refers to any kind of hosted service delivered over the
   internet. These services including servers, software, networks, databases, analytics and other
   computing function can be operated through the cloud.
4. Cognitive computing
   Cognitive computing is the term which is emerging typical cases of intelligent computing
   methodologies and systems that implements computational intelligence by autonomous
   inferences and perceptions mimicking the mechanisms of the brain.

Benefits of IIoT/Industry 4.0

• Productivity. In simple terms, Industry 4.0 technologies enable you to do more
  with less.
• Improved Efficiency.
• Increased Knowledge Sharing and Collaborative Working.
• Flexibility and Agility.
• Makes Compliance Easier.
• Better Customer Experience.
• Reduces Costs.
• Creates Innovation Opportunities.

Application Of Industry 4.0

Main objective of industry 4.0 is to increase the automation so as contribute to the
operational efficiency and effectiveneeso0f the company. Industry 4.0 based on the
integration of new technical solutions.

Industrial application can be of different types, such as process control manufacturing
automation, and energy management and application.

FACTS

Industry 4.0 fosters what has been called a “smart factory”. Within modular
structured smart factories, cyber-physical systems monitor physical processes, create a
virtual copy of the physical world and make decentralized decisions. Over the Internet of
Things, cyber-physical systems communicate and cooperate with each other and with
humans in real-time both internally and across organizational services offered and used by
participants of the value chain.
Smart manufacturing is a broad category of manufacturing that employs
computer-integrated manufacturing, high levels of adaptability and rapid design changes,
digital information technology, and more flexible technical workforce training. Other
goals sometimes include fast changes in production levels based on demand, optimization
of the supply chain, efficient production and recyclability. In this concept, as smart
factory has interoperable systems, multi-scale dynamic modelling and simulation,
intelligent automation, strong cyber security, and networked sensors.
Big data processing Smart manufacturing utilizes big data analytics, to refine complicated
processes and manage supply chains. Big data analytics refers to a method for gathering
and understanding large data sets. The definition of smart manufacturing covers many
different technologies. Some of the key technologies in the smart manufacturing
movement include big data processing capabilities, industrial connectivity devices and
services, and advanced robotics.

Challenges

Now that we speak about competitive benefits and customization, we also need to tackle
agility, scalability and flexibility. The same scalability and agility which we expect from
supporting IT services and technologies, such as the cloud are expected in manufacturing.
This is partially related with the previous topic of customization but mainly is about
leveraging technologies, Big Data, AI, robots and cyber-physical systems to predict and
meet seasonal demand, fluctuations in production, the possibility to downscale or upscale;
in other words: all the adjustments that are sometimes more or less predictable, can be
made more predictable or are not predictable but can be handled thanks to increased
visibility, flexibility and a possibility to leverage assets in function of optimal production
requirements from a perspective of time and scale. The development of innovative
capabilities and new revenue models. Digital transformation, as you can read in our
digital transformation strategy overview, is a matter of many levels, steps and capabilities.
You can transform processes, specific functions, customer service, experiences and
skillsets but in the end true value is generated by tapping into new, often information intensive, revenue sources and ecosystems, enabling innovative capabilities, for instance
in deploying an asa service capacity for customers, advanced maintenance services and so
on.

Conclusion :
In Industry 4.0, more than ever before, it is the key to success. Germany is well placed to
take a leading role in the provision and implementation of Industry 4.0 solutions. The
central government and federal states have launched strategic initiatives to drive its
development. Initiate all sector to need implement the industry 4.0 to making the
simplicity, and improve the productivity.