Bats use echolocation to see objects in front of them. They emit an ultrasonic pulse around 20 kHz (and up to 100 kHz) and then sense the pulses as they reflect off an object and back to the bat. It’s the same type of mechanism used by ultrasonic proximity sensors for object-avoidance. Humans (except perhaps the very young ones) can’t hear the ultrasonic pulses since the frequency is too high, but an inexpensive microphone in a simple bat detector could. As it turns out bat detectors are available off the shelf, but where’s the fun in that? So, like any good hacker, [WilkoL] decided to build his own.
[WilkoL’s] design is composed primarily of an electret microphone, microphone preamplifier, CD4040 binary counter, LM386 audio amplifier, and a speaker. Audio signals are analog and their amplitudes vary based on how close the sound is to the microphone. [WilkoL] wanted to pick up bat sounds as far away as possible, so he cranked up the gain of the microphone preamplifier by quite a bit, essentially railing the amplifiers. Since he mostly cares about the frequency of the sound and not the amplitude, he wasn’t concerned about saturating the transistor output.
The CD4040 then divides the signal by a factor of 16, generating an output signal within the audible frequency range of the human ear. A bat signal of 20 kHz divides down to 1.25 kHz and a bat signal of up to 100 kHz divides down to 6.25 kHz.
He was able to test his bat detector with an ultrasonic range finder and by the noise generated from jingling his keychain (apparently there are some pretty non-audible high-frequency components from jingling keys), but hasn’t been able to pick up any bats as yet. Maybe somewhat ironically, there aren’t a ton of bats in his neighborhood.
Anyway, we’re definitely looking forward to seeing the bat detector in action! Who knows, maybe he’ll find Batman.
How Artificial Intelligence is Changing the eLearning Environment
Artificial intelligence (AI) is everywhere these days, making inanimate objects increasingly smart. It’s designed by humans for humans, to enrich and facilitate our everyday lives. As a matter of fact, AI is now the brain behind your smartphone, car, music streaming service, banking app, freezer, and travel agency. It’s not only omnipresent, it’s omniscient as well.
If the main keyword for AI is “smart”, then how come we don’t talk more about this burgeoning technology in the context of knowledge, learning, and education? AI has everything we need to revolutionize the industry, enrich and facilitate the learning experience of students and adult learners, and boost the knowledge retention rates across the board.
It’s a whole new chapter in the history of the classroom. The change has already begun, with AI reshaping eLearning as we know it. Find out how.
AI Makes Personalized Learning a Child’s Play
Every student is different. Educators have known this for a long time, but it wasn’t until LMS software solutions that they were able to actually accommodate the various needs of different types of learners.
The introduction of technology to the traditional classroom established a framework for blended learning, which is now the dominant model for educating modern-day students. Essentially, blended learning allows students to choose how they access educational content, and how they acquire knowledge in terms of learning styles and speed. But AI brings personalization to a whole new level.
Unlike teachers, artificial intelligence can recognize students’ learning needs, interests, preferences, habits, and capacities automatically and in real-time, by analyzing their performance. This powerful insight helps create highly personalized learning environments and paths where every aspect – from content type to delivery method – is adjusted to the students’ individual needs.
The result? Optimum performance of every learner.
AI is at Learners’ Disposal Anytime, Anywhere
In combination with personalized learning paths, unlimited connectivity makes it possible for students to access educational content from anywhere and at any given moment.
Adaptive learning environments enable and encourage self-paced learning, thus allowing students to make the best out of their peak productivity hours. But what happens if one learner’s productivity peaks in the middle of the night, when there’s no one around to help solve a dilemma or address points of confusion?
Since blended learning is a combination of instructor-led training and online courses, tutors should remain available 24/7, whenever students may need their guidance. This may not be possible with human tutors, but it is with digital assistants.
Thanks to machine learning and natural language processing, AI assistants can learn to provide necessary guidance to students, answer their questions, and solve their problems. And since machines never sleep, this digital mentorship is available 24/7.
Digital Mentorship Can Encourage Engagement
Usually, AI assistants work with students individually. Extending the concept of student-centered education, smart technology caters not only to different learning styles but also to different personalities and temperaments. This is significant to introverted students, who usually don’t feel comfortable expressing themselves in front of their peers in the traditional classroom environment.
Faceless AI is a saving grace for such learners as it allows them to voice their dilemmas without the fear of being judged, while the eLearning environment itself encourages them to participate in social learning. Of course, AI has the potential to motivate and engage all students, be they introverts or extroverts, visual learners or auditory learners.
Higher engagement is a natural consequence of personalization – by facilitating the learning path, AI makes knowledge acquisition easier, thus eliminating all frustration from the process. All students thrive in such a learning and development (L&D) environment when they are motivated by their own achievements.
AI Allows Continual Real-Time Improvement
Thanks to cutting-edge software technology and authoring tools, everyone can learn to create an online course that encourages engagement and equips students for success.
It’s maintaining this eLearning environment that’s hard, especially in today’s fast-paced world. Technology is a powerful knowledge acquisition tool – the more potent it becomes, the more we understand about the world we live in. The human race is learning on a daily basis.
The road from tacit to explicit knowledge was a long one in the pre-digital age. At times, students had to wait years before new findings were added to their old textbooks. Today, we have the Internet – the biggest and fastest knowledge base in history.
With AI, we can now comb through this knowledge base in matters of minutes, update our online courses with cutting-edge information in real time, and keep educational content relevant. Having said that, up-to-date content is not enough to ensure a rich learning experience. Educators and online course creators must learn from their students as there are always challenges that need to be addressed. Because of this, student feedback is precious.
Real-Life Examples of AI in Learning
Let’s now see a few companies who are working behind the scenes to bring the benefits of AI-powered technologies to people.
Massachusetts-based software technology company, Nuance builds speech recognition software. The technology can transcribe a maximum of 160 words per minute. It is useful especially to learners with mobility challenges, including writing. Instructors too can rely on it to dictate classroom lectures and expedite repetitive tasks such as emails.
As a provider of quality math education, Carnegie Learning brings together artificial intelligence and machine learning to its platform. It puts emphasis on personalized learning experiences to turn learners into critical thinkers, creative problem solvers, and lifelong learners. By combining cognitive and learning science with research and practical instructions, CL helps students gain a deeper understanding of what they are learning.
Century is a provider of an AI-based teaching and learning platform located in London. It provides adaptive learning solutions for learners according to their strengths and weaknesses, while helping instructors simplify their routine tasks such as grading. For this, it combines AI, neuroscience, and data analytics.
Artificial intelligence is already making waves in the eLearning industry by unlocking exciting new opportunities for educators and students alike. But deep personalization, 24/7 availability, increased engagement, and real-time improvement are only a fragment of what AI may mean for the future of education. Experts predict that the use of this smart technology will grow by 47.5% in the next two years. We can only imagine the possibilities.
IoT Security Concerns in the Media and Entertainment Industry
The Media and Entertainment industry is bigger than ever, and it has been spurred in growth somewhat by the development of new technologies. As with any other industry, Media and Entertainment significantly benefit from collecting data and increasing connectivity.
Here are three main use cases where IoT comes into play in the Media and Entertainment industry:
Increase Customer Base and Profitability
- Build enhanced view of customers and customer household preferences by leveraging data from wearable devices to mobile & social media data
- Develop or acquire content that meets targeted needs of the customer base for improved profitability
Grow Advertising Revenue
- Leverage rich customer preference information for targeted and effective advertising and hence increasing the revenues
- Retain advertisers by moving to most appropriate channels by analyzing customer preferences around content and delivery mechanisms
- Effective and targeted promotions and marketing efforts
Effective Operations and Multi-Channel Differentiation
- Electronic bracelets and sensors to track customers’ movements at theme parks and on cruises for greater customer experience and differentiated experience
- Improve customer service and differentiation through better visibility into customer content and entertainment preferences
- Preventive maintenance and optimal utilization of media equipment and archived content based on sensor data
While IoT is changing the way the industry is operating by helping it manage and use valuable data, this improvement is not without its risks. Media and Entertainment companies are high-profile targets for cyber attacks, and often unintentionally provide malicious attackers plenty of opportunities to carry out their attacks. Let’s have a closer look at the state of the Media and Entertainment industry and main IoT security concerns.
The Media and Entertainment industry is unique in many ways, and that can make it quite tempting for cyber attackers. The use of data is very prominent, and crucial for media and entertainment companies to figure out what the customers want. However, it’s also one of the industries where success can depend a lot on personal relationships between the business partners. In those circumstances, keeping a reputation of a secure and trustworthy company is essential to increase revenue.
For the creative product or process to be developed and distributed, Media and Entertainment industry companies need sensitive data. The industry uses outside vendors extensively, where IoT is undoubtedly helpful. However, the complexity of these processes of production can sometimes leave the company less than able to protect its assets.
According to a Hiscox survey, over a 12-month period more than half of all surveyed Media and Entertainment companies found themselves under three or more cyber attacks. Those are significantly high numbers, especially when it’s taken into account how much sensitive data these companies are managing. Meaningful insights into consumer behavior and preferences are valuable, as well as personal and financial data.
Outside vendors are also being targeted, compromising the security of the entire supply chain. Cyber attacks are set to become a norm and much more frequent if the main cybersecurity concerns for the Media and Entertainment industry aren’t addressed.
Since the fast and furious advancement of IoT has created blind spots that cybersecurity needs to address, it’s no wonder why there are particular security concerns that some other industries don’t have to face. A good cybersecurity solution should aim to improve an enterprise’s safety in three key areas:
- Prevention — correctly assessing the risks and vulnerabilities, keeping cybersecurity a priority in any project and training staff on recognizing malicious attacks;
- Detection — tracking all attempted attacks, coming up with a response plan in case of discovery and making sure the employees will report any intrusions in the system;
- Mitigation — an extensive program to prevent or detect, contain and assess cyberattacks, testing all systems for weaknesses, and continuously reviewing security.
Solving Security Concerns
One of the main points that the Media and Entertainment industry has to address is the overestimation of security and underestimation of risk. Without professional cybersecurity protection and testing systems in place, it’s safe to assume that a company could be doing more to protect its assets. The risks are significant and need to be taken seriously.
If we wish to ensure IoT security in every industry, it’s essential to take a detailed look into any product’s or system’s security and make sure that it’s up to the highest security standards relevant to the operational environment of the industry in question.
The Future of IoT Deployments in a Post-COVID World
With over 14 million cases globally, COVID-19 has caused significant disruption across all sectors, including IoT. Delays to physical roll-outs and maintenance of IoT devices and networks are occurring globally with varying travel restrictions and lockdown measures.
While the pandemic initially slowed the manufacturing, distribution, and implementation of IoT projects, it also effectively demonstrated how reliant our society is on the technology that keeps us connected. IoT device adoption in supply chains will play a role in mitigating future disruption caused by the virus, as well as making processes more efficient to get roll-outs back on track.
Required Evolutions for IoT Roll-Outs
Industrial Internet of Things (IIoT) networks are often expansive and have been designed to scale with growing operations. These IoT networks often consist of a large number of small form factor devices such as sensors and processors that require engineers to install and connect to each IoT device. As opportunities for physical site visits to provision a device have been limited throughout the pandemic, further deployments have been reduced.
As seen in Figure 1, the total number of cellular IoT devices is forecasted to reach 1 billion by 2024; rising from over 320 million in 2020. However, the embedded SIM (eSIM) has created the need for new frameworks for cellular IoT roll-outs; these frameworks need to account for the varying requirements of service providers in the industrial, enterprise, and consumer IoT markets.
With companies tightening their belts as the economic impact of the pandemic hits, cellular IIoT can help bring cost savings. Devices in the IIoT often only require limited connectivity, such as Low Power Wide Area (LPWA) that leverages low duty cycles to connect to the network. This low cost per connection is increasing the popularity of these cellular connections, although current roll-out procedure complications have limited growth.
Hardware vendors are also increasingly looking to reduce the size of their devices. This trend is most notable in LPWA equipment as they have fewer hardware requirements. The small form factor often means that the implementation frequently requires specialist tools as any built in user interface is not included on the device. Embedded modules and management platforms that create new frameworks are tools that can enable a smoother deployment and allow for remote management.
For traditional SIMs, much of this implementation process is still done at the physical location at which the device will be located during its operational lifetime. Remote SIM Provisioning (RSP), enabled by embedded modules, means that a large degree of this process can be done before any implementation at a central location where multiple devices can be configured at once. Once the unit is in the correct location, RSP enables it to be connected to cellular networks with minimal physical interaction. This reduces the demand for specialist engineers that need to implement a multitude of devices spread out across a large geographical area; a process that would have been made increasingly difficult during the early stages of the pandemic.
The learning curve currently facing the market has evidently been accelerated by the impact of COVID-19. The heightened emphasis on the benefits of IoT connectivity has essentially forced IoT service users to adapt to these new frameworks because they were unable to use the existing processes that they were accustomed to.
Post COVID-19 Cellular IoT Roll-outs
It is important to note that cellular IoT roll-outs have continued throughout the pandemic, but at a slower rate as IoT service users became increasingly hesitant about plans. As a result, the aforementioned ‘learning curve’ with remote provisioning of IoT devices has needed to accelerate as IoT service users switch to use remote services for IoT roll-outs.
We should view this as an ongoing opportunity for eSIMs in the industrial and enterprise space, with IoT service users no longer locked into long-term connectivity contracts with a sole operator. As the prevalence of embedded modules increases, so does the fairness of pricing and the flexibility available to these end-users.
There are some steps to fully exploiting the benefits of the embedded module:
- Migrating the remote provisioning process to a centralized online platform that can be accessed by multiple users. This is essential as these networks can comprise thousands of connected devices, and will only continue to grow. Remote provisioning enables standardized updates across the whole network and for individualized management of portions of the network, based on a user’s needs.
- Verifying and authenticating connections must be seamless and integrated into remote management services. Early IoT services used proprietary authentication services which developed into a market that had a high degree of fragmentation when it came to large scale deployments. We have seen numerous scenarios unfold in which devices would not be able to authenticate properly and thus provided security risks to the end-user.
- Utilizing devices based on cellular IoT standards is critical. As the number and scale of IoT networks increases, the efficiency of the provisioning process must increase to handle the future acceleration of the growth of IoT roll-outs. Offering services that can cater to the many different use cases in the IoT market means that products and devices need to share a common core of protocols in order to remain interoperable and manageable.
The importance of IoT ecosystems at all levels, including the device, network, and applications, cannot be understated. As the benefits of leveraging cellular networks for IoT purposes become more well-known, we will see an increasing amount of previously unconnected devices becoming part of IoT networks. The need for secure and reliable connections will continue to grow over the next five years, as the demand for real-time monitoring and management of operations increases. In turn, this will escalate the demand for comprehensive solutions that can manage the roll-outs of these devices across increasingly complex IoT networks.
How Could IoT Deployments Assist in Mitigating the Impacts of the Pandemic?
eSIMs can provide flexibility and scalability for IoT global deployments. They are programmable over-the-air, which supports current demands by seamlessly transitioning between various network subscriptions in real-time. With the right provider, eSIMs can offer complete connectivity with a large range of options so that, regardless of the country of deployment, multinational SIMs or local profiles are available to assist in the launch of IoT networks.
The ongoing pandemic is likely to provide several ‘learning opportunities’ for the cellular IoT market. Most notably, there is a need for more efficient cellular IoT deployments, to enable easy remote management and reduce operational costs in an uncertain economic climate. However, the ecosystem contains several stakeholders who all need to continue to collaborate on these processes to maximize their potential.
The pandemic has highlighted the benefits of cellular IoT technologies, particularly where remote environments are concerned. Educating the stakeholders on these benefits and the return on investment that can be accomplished will lead to accelerated adoption in sectors including healthcare, smart cities and agriculture.
Healthcare is the most notable sector that could have benefited from larger IoT presence during the early stages of the pandemic, particularly the ability to monitor citizens and early symptoms. The real benefit of taking this approach is the availability of data and the time it takes to be delivered. A key issue facing IoT adoption in the healthcare industry is the disparate systems in use in multiple countries, and in the worst cases, within the same country itself. IoT services within the industry have the potential to unify these systems to a certain degree. This global pandemic should be viewed as an opportunity to assess the future of healthcare industries; a future that needs to be centred on the potential advantages that IoT technologies can bring.
Evolving Operator Roles in Cellular IoT Deployments
Operators are increasingly moving away from a Capital Expenditure (CAPEX) model towards an Operational Expenditure (OPEX) model. This is most apparent in the deployment and expansion of 5G networks, which has highly reliant software-defined network components compared to previous cellular technologies. Despite the severe global disruption in the first six months of COVID-19, MNOs have pressed on with their 5G networks. By 2025, 5% of 5G connections are anticipated to be attributable to IoT, representing a revenue opportunity of $8 billion in that year.
Operators have already identified growth in cellular IoT demand, with Tier 1 operators setting up programs to encourage the development of eSIMs in IoT devices. This collaboration between operators and other stakeholders has been key to increasing the impact of eSIMs on IoT markets.
Many recent operator IoT efforts have focused on consumer devices. The IIoT market provides different challenges, market drivers and opportunities than the consumer aspect of the IoT. As a result, we’ve seen different sets of hardware vendors, end-users and use cases emerging. However, the operators remain the constant provider of the underlying cellular connectivity that all devices will operate with.
Looking to the Future
It has been said that one of the lasting impacts of the pandemic has been to accelerate digitization. That necessity has forced innovation in unexpected spaces in the IoT, and also shows how cellular IoT in particular can really help lessen the impact of movement restrictions.
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