IoT Security
Article | July 17, 2023
If you’re struggling with creating a value proposition in volatile markets, you’re not alone. According to Neil Patel, 40% of marketers struggle to acquire leads by traditional marketing methods. As competition grows in each industry, even fairly monopolistic markets like tech are seeing rising competition in all areas.
To combat market uncertainty, as well as stand out amongst your competitors, you need a market strategy that not only offers a direction but actively targets your goals. A market strategy is your go-to plan when things get rough and it is a map for when the waters are calm. Moreover, marketers with a documented strategy are 313% more likely to report success.
We’re sure you already have a market strategy that is just right for you. But have you considered if it can be refined further? Thanks to emerging technologies like IoT, we now have access to the most mundane customer decisions that are taken on a day-to-day basis. This data is your ticket to a better market strategy without having to spend a bomb.
This is how you can refine your market strategy with the help of IoT.
Data-driven Decisions
The Internet of Things has offered us insurmountable amounts of consumer data. A caffeine brand can now access information such as what time consumers have coffee, whether it is at home or office, what flavors they prefer, how much they’re willing to spend on coffee, and what other alternatives they consume. This kind of data, collected on an IoT device such as a coffee machine, is instrumental in making marketing decisions. If you know that your consumer prefers to have coffee at work in peace rather than in a rush at home, you can target offices in the area with your product rather than targeting individual consumers.
IoT offers you the right information to make the right decisions. But you can also leverage this data to drive your market strategy. In the above example, the marketing team can account for campaigns geared towards workplaces based on the available data in the budget. Data-driven strategies prove to be more effective than otherwise, and as marketers, you must absolutely leverage any IoT data that may be relevant.
Respect your Customers
While IoT offers marketers a truly astounding amount of data, not all users are aware of what data is being tracked. This raises concerns for privacy and security among the users. Even though most of the users waive their rights to withhold the information when signing into an app or wearables software, they are not always comfortable sharing certain data.
As marketers, it is important to keep your practices ethical and legal. Using consumer data may be completely legal, but it is best not to offend your customers by overt use of data that they aren’t comfortable sharing. Make sure that the usage of data in marketing campaigns and strategy is limited to what data has been consciously shared by your consumers. This will bolster your goodwill, as well as make your customers trust your brand.
Offer Valuable Solutions
With the advent of Big Data and AI technologies, the internet of things is turning over a new leaf. As there is a vast amount of data that can be processed fast with AI, marketers can now target individuals rather than households or groups. With precise data available over consumer decisions and actions, it is possible to know if there are any unlikely customers that you have been ignoring so far.
IoT allows you to not only target these customers but also solve their problems. If we continue the caffeine example, the connected coffee machine can tell you when the coffee is about to be over, this can send you reminders to buy coffee, or in case of further automation, place an order on Amazon on your behalf. These solutions can be now hyper-personalized to suit individual needs through IoT.
IoT Based Campaigns
Your market strategy will have to account for campaigns throughout the year, but if you’ve noticed closely, the only marketing campaigns that gain significant traction are the ones that have a ‘wow factor’. A lot of marketers mistake the wow factor to be a subjective preference that customers have but it couldn’t be further from the truth. The wow factor is simply the effect produced when a business goes above and beyond to meet customer needs. IoT offers us the resources required to manufacture the wow factor in every single campaign.
A great example of this phenomenon is beacon marketing. Beacon marketing is considerably new in the marketing industry and uses Bluetooth technology to transmit information to nearby mobile devices. It is heavily used in retail across the globe and giants like Target and Walmart are already using the technology to market its services. Walmart places beacons in its lights across its stores and sends offers to its customers based on their location. It not only personalizes the shopping experience, but also saves a large amount of electricity bill for its stores.
Target Existing Customers
Many times, in a bid to appease new customers, marketers often forget about their existing customers. Your existing customers already know you, have tried your product or service, and are clearly interested in the product. A good product or service is often enough to keep the customers returning, but with the current levels of competition, customers often find themselves wondering if they should try new things. As a marketer, all you need to do is deter your existing customers from straying. You can do this by either providing an unparalleled service, which is quite unlikely in today’s market, or you give them a reason to stay.
Thankfully, targeting existing customers is much easier than targeting new ones. You already have their data over their preferences and habits. If you know that a certain firm updates their applications every second quarter, you can send them offers just before the second quarter starts and remain fresh in their memories when they decide to make the decision.
Allergy medication Zyrtec leveraged IoT when targeting their existing customers with a voice-enable application. Its users could just ask the application about the daily allergens and pollutants in their area so they could prepare ahead. The app offered a powerful solution to its users while making great use of its brand image and retaining almost all of their existing customers.
Leverage New Technologies
We have already discussed several complementary technologies to IoT that can help you make the most out of your market strategy. AI and Big Data are some of the strongest allies for IoT that can help change the norms across industries. But even limited technologies like voice-enabled applications, QR scanners, beacons and so can open up a lot of opportunities for marketers.
Consider adopting some of these technologies such as geofencing which are inexpensive and effective at the same time. Burger King is a great example of using geofencing for marketing. Geofencing is a technology wherein you can transmit messages or information to mobile devices within a certain area. Burger King set up their geofences across all McDonalds in the UK and as soon as anyone entered within a 500 m radius of a McDonald’s outlet, they received Burger King coupons and directions to the nearest store.
Case Studies
There are a lot of examples of IoT being used to enhance strategies or campaigns. Some of these examples are given below.
Diageo, a whisky brand in Brazil innovatively used IoT to run a father’s day campaign. They encouraged men to buy whisky for their fathers and placed a QR code on their bottles. Once the bottle was received, the fathers could scan the code which would play a personalized father’s day message by their sons. This concept was so loved by people in Brazil that Diageo saw a 72% sales uplift in the two weeks leading up to Father’s Day.
South East Water, CRM leveraged IoT by building an end-to-end IoT ecosystem powered by IBM’s Maximo. This helped them roll out an app that offered near real-time insights into customer requirements for over 80 engineering teams. This alone helped them ensure higher customer satisfaction and accelerated access to critical reports by 99 percent!
Uber and Spotify rolled out an IoT campaign together wherein you could access your Spotify playlists through the Uber app and once you were in an Uber, you could play whatever you liked through the app and it would play on the car’s speakers. This increased customer satisfaction for both Uber and Spotify users.
There are several examples of using IoT in marketing campaigns, and there is never a dearth of ideas. However, in order to appeal to your unique customer base, you need to innovate your product with IoT.
Frequently Asked Questions
What is the IoT strategy?
IoT Strategy refers to an organization’s strategy to inculcate IoT in their business, whether as a marketing tool or as an integral part of the process.
How does IoT affect the marketing industry?
IoT offers a lot of insights and resources to marketers which helps them target their customers better and optimizes any marketing efforts, thereby effectively obliterating traditional marketing practices.
What is the best internet of things marketing strategy?
There is no one IoT marketing strategy that fits all businesses. Each business needs to identify its customer requirements and strategize accordingly.
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IoT Security
Article | June 27, 2023
Artificial intelligence (AI) has already made headway into becoming a general-purpose technology vastly impacting economies. Yet, the interpretation and estimated trajectory for something remotely close to what we call AI now was first explored in the 1950s.
Until this very day, AI keeps on evolving further. Though let’s face it, AI would have been useless without data. With around 2.5 quintillion bytes of data being generated every day, the numbers will shoot up as the Internet of Things (IoT) enters the game.
Let’s see what this is all about and where and how exactly IoT crosses paths with AI applications.
IoT fundamentals: Where does IoT meet AI
The benefits of IoT in AI
Challenges of IoT in AI
Why implement machine learning in IoT
IoT applications for AI
Key takeaways
IoT fundamentals: Where does IoT meet AI?
What is meant by the term internet of things (IoT) is essentially a system of correlated digital and mechanical appliances, computing devices, and sensors embedded often into everyday objects that transfer data over a network. IoT connects the internet to any and every physical thing or place in the world.
Modern IoT has advanced from the mere merging of microelectromechanical systems to wireless technologies, and faster data transfer through the internet. This resulted in a confluence of information technology and artificial intelligence, allowing unstructured machine-generated data to be evaluated for insights that could lead to new developments.
More and more industries are now referring to IoT to function more proficiently, provide better customer service, escalate the significance of their business, and implement robust decision-making.
Machine learning for IoT can be used to identify anomalies, predict emerging trends, and expand intelligence through the consumption of audio, videos, and images. The implication of machine learning in IoT can substitute manual processes and offer automated systems using statistically backed up actions in critical processes.
The benefits of IoT in AI and real life
IoT offers the following benefits to AI applications:
IoT data for business purposes
Cost and time savings
Task automation and reduction of human intervention
Higher quality of life
IoT data for business purposes
IoT can also be viewed as a data pool. That means by aggregating IoT data, one can extract useful data-driven feedback, which in turn (used properly) may foster effective decision-making. Businesses can also identify new market opportunities, not because of IoT itself but by using the data IoT provides. And since IoT offers companies access to more data, and hence advanced analytics of that data, its usage can eventually result in improved customer outcomes and enhanced service delivery.
Cost and time savings
When devices get connected, cost reductions come along with it. The gathering of different data allows for advances in efficiency, and it leads to money surplus and low-cost materials.
Task automation and reduction of human intervention
Nowadays, devices that are internet-connected can be found in every aspect of our lives, and it is safe to say that they make tasks easier. These automation features range from real-time AI-powered chatbots to home automation control systems, and all of it usually takes a click of a button.
For businesses offering AI-enabled solutions, similar advancements can be achieved with pipeline automation too. That includes significant cuts in annotation and QA time. By leveraging SuperAnnotate’s platform, hundreds of companies recorded faster task completion and more accuracy in prediction results.
Higher quality of life
IoT is not only beneficial in the business aspects but it also creates better living circumstances for us. Smart cities and agriculture, intelligent homes, and food waste solutions are some of the most common ways of IoT providing better, more sustainable living conditions for people.
Challenges of IoT in AI
Despite the numerous benefits and advancements that IoT brings to the table, there have been a few limitations with it. Some of them are listed below:
Privacy issues
Data overflow
Bug issues
Compatibility issues
Privacy issues
With the increased connection between multiple devices or their coexistence for model development purposes, more information is shared between them, which poses vulnerability to your data and makes room for caution. Added layers of protection are needed to prevent risks of data leaks and other threats.
Data overflow
Eventually, organizations will have to find a way to deal with the large numbers of IoT devices, and that will include the collection and systematic management of all the data from those IoT devices. The proper use of data lakes and warehouses, close governance, and intuitive arrangement of datasets will become an utmost priority.
Join hundreds of leading companies who build super high-quality training data up to 5x faster using SuperAnnotate’s intuitive data curation and robust project management features.
Bug issues
If one IoT device has a bug in its system, there is a large chance that every other connected device will also have it.
Compatibility issues
Because there are no international standards of compatibility for IoT, it's harder for different devices to communicate with one another.
Why implement machine learning in IoT
More and more companies are combining IoT with machine learning projects so they can achieve analytical skills on a large variety of use cases which allows their businesses to have access to fresh insights and adopt innovative automation. By implementing machine learning for IoT, they can leverage the following:
Convert data into a coherent format
Arrange the machine learning model on device, edge, and cloud
Enable use of data on edge devices directly for complex decision making
IoT applications for AI
Although we have covered the basics of IoT, its implications for AI are not as simple. Many corporations are adopting IoT which allows them to have an advanced approach to growing and advancing their business. Novel IoT applications are offering organizations the ability to plan and implement more vigorous risk management strategies. Some of the more common uses of IoT in AI encompass the following:
Transport logistics
Not only does IoT expand the material flow systems in transport logistics, but it also improves the automatic identification and global positioning of freight. It also increases energy efficiency and consequently declines the consumption of energy.
Smart cities
Although the term smart city is still incomplete, it mainly refers to an urban area that endorses sustainable enlargement and high quality of life. Giffinger et al.’s model explains the features of a smart city, including the people, the government, the economy, and lifestyle.
E-health control
The two main objectives of future health care are e-health control and prevention. People nowadays can choose to be monitored by physicians even if they do not live in the same country or place. Tracing and monitoring peoples’ health history makes IoT-assisted e-health extremely useful. IoT healthcare solutions could also benefit the specialists, as they can collect information to advance their medical calculations.
Key takeaways
Ever since its development, IoT, especially AI-enabled IoT, as discussed, has been enhancing our daily lives and directing us to work smarter while having complete control over the process. Besides having smart appliances to elevate homes, IoT devices can also be essential for providing insights and an actual look for businesses into their systems. Heading forward, IoT will continue to develop as more organizations get to understand its potential usage and tangible benefits.
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Security, IoT Security
Article | July 13, 2023
Discover the crucial role of big data capabilities in unlocking the potential of IoT for businesses. This article covers their synergy, challenges, and value in decision-making and revenue generation.
Contents
1 Why Big Data and IoT Matter for Businesses
2 Understanding Synergy of Big Data and IoT
2.1 How IoT generates Big Data
2.2 Challenges of Processing Big Data from IoT Devices
2.3 Importance of Big Data in IoT Applications
3 The Value of Big Data and IoT for Businesses
3.1 Improved Decision-making for Businesses
3.2 Generate New Revenue Streams
4 Final Thoughts
1. Why Big Data and IoT Matter for Businesses
The internet of things (IoT) is connecting all types of physical assets to the internet, from smart wearables that track wearer’s vitals to connected industrial units that can report any malfunctions automatically. Big data in IoT is a natural outcome with the growth of IoT devices, with an immense surge in the amount of data being generated.
There are currently over 13 billion connected IoT devices worldwide.
(Source – Techjury)
This data is extremely valuable to businesses as it can help streamline operations, predict trends, and diagnose device issues. Certain functions of IoT devices that are crucial for modern businesses, such as enabling predictive maintenance, depend on the analysis of the data generated every second. However, to maximize the ROI from their IoT ecosystem, businesses must first manage and process the vast amounts of unstructured data they produce. This is where big data capabilities come in.
2. Understanding Synergy of Big Data and IoT
Big data and the IoT are fundamentally different concepts, but are closely connected. Big data is a term that is used for a great amount of data that is characterized by volume, velocity, variety and veracity (or the ‘trustworthiness’ of data). The IoT is a term for physical devices or objects linked to the internet using an assortment of technologies. Understanding the synergy between these two technologies will be critical for businesses looking to leverage their full potential.
2.1 How IoT generates Big Data
IoT is one of the primary drivers of big data growth. The vast number of interconnected devices in the IoT ecosystem generates a massive amount of data every second. This data includes information on user behavior, device performance, and environmental conditions, among others.
The nature of this data makes it challenging to store, process, and analyze using traditional data management tools. This is where big data technologies such as Hadoop, Spark, and NoSQL databases come in, providing the ability to manage massive amounts of data in near-real-time, enabling critical applications of big data in IoT. For businesses, processing IoT data is synonymous with processing big data, due to the nature of the data generated by an IoT ecosystem.
2.2 Challenges of Processing Big Data from IoT Devices
IoT data processing is a complex and challenging task due to several reasons. Firstly, the sheer volume of data generated by these devices is enormous and is only increasing. This requires a robust infrastructure and specialized tools to store, manage, and analyze the data efficiently.
This data is also generally unstructured, heterogeneous, and complex, making it difficult to process using traditional data management and analysis techniques. Moreover, it is often noisy and may contain errors or outliers, which can impact the accuracy of data analysis. Businesses also face a challenge when securing such vast amounts of data. Since IoT devices collect sensitive information such as personal and financial data at scale, it is critical to ensure that data is encrypted, transmitted securely, and stored safely.
Additionally, IoT devices often operate in remote locations with limited connectivity, making it challenging to transmit data to the cloud for storage and analysis. As IoT devices continue to proliferate and generate increasingly large amounts of data, businesses must adopt big data technologies to gain actionable insights from this data.
2.3 Importance of Big Data in IoT Applications
There are several use cases of the IoT where processing large amounts of data is essential. It plays a critical role in IoT applications, providing businesses with valuable insights that can be used to optimize processes, reduce costs, and improve overall efficiency. By collecting and analyzing large amounts of data from IoT devices, businesses can gain a better understanding of customer behavior, machine performance, and other critical metrics.
For example, big data in IoT can be used to identify patterns in customer behavior, allowing businesses to tailor their marketing efforts and improve customer engagement. Additionally, IoT devices can be used to collect data on machine performance, allowing businesses to identify potential problems before they occur, minimize downtime, and optimize maintenance schedules. The value of big data in IoT applications lies in its ability to provide businesses with real-time insights that can be used to drive growth, reduce costs, and improve overall efficiency.
3. The Value of Big Data and IoT for Businesses
Businesses looking to integrate big data in IoT must first consider their data storage and analytics capabilities. By understanding the value of big data technology in capturing and analyzing IoT-generated data, businesses can unlock insights that can help them make better decisions, optimize processes, and create new business opportunities.
3.1 Improved Decision-making for Businesses
IoT and big data technologies offer businesses a wealth of data that can be used to make better-informed decisions. By integrating IoT sensors and devices with their operations, businesses can collect real-time data on customer behavior, operational performance, and market trends. This data can then be analyzed using big data analytics tools to generate valuable insights that can inform decision-making.
For example, operational data can be analyzed to identify inefficiencies and areas for optimization, helping businesses reduce costs and improve efficiency. With the right data storage and analytics capabilities, businesses can leverage the power of IoT and big data to gain a competitive advantage and make better-informed decisions that drive growth and success.
3.2 Generate New Revenue Streams
By leveraging the vast amount of data generated by IoT devices and analyzing it with big data analytics tools, businesses can gain insights into customer behavior, market trends, and operational performance. These insights can be used to create new revenue streams and business models, such as subscription-based services, pay-per-use models, and predictive maintenance services.
For example, IoT sensors can be used to collect data on equipment performance, allowing businesses to offer predictive maintenance services that help prevent equipment breakdowns and reduce downtime. Similarly, customer data can be analyzed to identify new revenue opportunities, such as personalized product recommendations and targeted advertising. With the right strategy and investment in IoT and big data technologies, businesses can unlock new revenue streams and create innovative business models that drive growth and success.
4. Final Thoughts
Big data in IoT is becoming increasingly important for businesses, and the future prospects are bright. As IoT continues to grow and generate more data, businesses that can effectively analyze it will gain a competitive advantage, leading to increased efficiency, reduced costs, and higher ROI. To fully realize the benefits of IoT, businesses must develop big data analytics and IoT devices in tandem, creating a feedback loop that drives continuous improvement and growth. By embracing these technologies, businesses can make data-driven decisions and unlock new insights that will help them thrive in the years ahead.
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Enterprise Iot
Article | June 2, 2022
Introduction
Automation, interconnectivity, machine-learning, and real-time data are part of Industry 4.0, a new phase in the Industrial Revolution. Industry 4.0, which includes IIoT and smart manufacturing, combines physical production and operations with smart digital technologies. It creates a more holistic and linked environment for manufacturing and supply chain management organizations.
In today's production environment, "automation" has a new, more advanced meaning than it has in the past. Industry 4.0 refers to the necessity of lean, efficient operations and the function of sustaining and improving production. In contrast, IIoT distinguishes manufacturing gadgets from consumer products that can connect wirelessly to internal networks and the internet.
IIoT Powering the Fourth Industrial Revolution
Manufacturing, logistics, oil and gas, transportation, mining, aviation, energy, and other industries use the IIoT. Its main goal is to improve operations, mainly through process automation and maintenance. IIoT capabilities improve asset performance and allow for improved maintenance management. The introduction of Industry 4.0 technologies marked a significant milestone in the human-machine relationship's history. I4.0 was first talked about in 2011. Since then, it has proliferated because of new technologies such as cyber-physical systems, IT/OT convergence, AI/ML, Blockchain, and AR/VR.
Data is at the heart of the Fourth Industrial Revolution. The growth of the Internet of Things (IoT) is one of the main reasons behind this. The IoT is making a significant contribution in making businesses smarter and improving their workflows. Moreover, more data is being made and used by connected devices than ever before, from the home to the factory.
In order to thrive in the fourth industrial revolution, businesses must embrace new technologies. The general structure of IIoT applications is defined by standards-based industrial system architectures such as the Industrial Internet Consortium's Reference Architecture. Sensors and IoT devices, IoT middleware platforms, IoT gateways, edge/cloud infrastructures, and analytics applications are all part of the stack.
The Future of the IIoT
The Industrial Internet of Things (IIoT) is primarily regarded as one of the most significant current and future trends influencing industrial companies.
To comply with new rules, industries are rushing to upgrade their systems, machinery, and equipment. This is necessary to keep up with market volatility and deal with disruptive technologies.
Safety, efficiency, and profitability have all improved dramatically in industries that have adopted IIoT. As IIoT technologies become more widely adopted, this tendency is projected to continue.
Conclusion
The fourth industrial revolution has drastically altered our perceptions of things in the workplace. At a rapid rate, capitalists are becoming more interested in sophisticated ideas.
The way forward is to embrace existing and emerging technology throughout fundamental operations to unleash more enticing possibilities. It emphasizes the importance of comprehending the impact collaborative ecosystems can have as well as how they will become a major differentiator for generating value with a better-trained workforce.
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