Category Archives: Internet of Things

The Future of Personalization: How the Internet of Behaviors is Crafting Individual Experiences

IOB Contextual Targeting

Throughout this blog series, we’ve explored various facets of IoB, from its application in smart cities to its role in behavioral analytics. By examining how IoB is revolutionizing personalization and enabling precision targeting, we aim to offer a comprehensive understanding of this burgeoning field. Whether creating tailored experiences or enhancing engagement through data-driven insights, IoB leads modern technological advancement.

In today’s digital landscape, the Internet of Behaviors (IoB) has become a transformative force, changing how businesses approach personalization and targeting. For tech executives, CMOs, CTOs, and business owners, understanding and leveraging IoB can provide a significant competitive edge. This blog delves into IoB’s profound effects on personalization and targeting and connects it to our previous discussion on behavioral analytics. Let’s explore how IoB is shaping future business strategies.

Introduction to IoB in Personalization and Targeting

IoB in Personalization and Targeting

As consumers interact with digital platforms, they generate vast amounts of data. IoB leverages this data to gain insights into user behaviors, preferences, and patterns. By analyzing these behaviors, businesses can craft highly personalized experiences that resonate with individual users. The result? Enhanced targeting, increased engagement, and improved conversion rates. This shift towards personalization is not just a trend but a necessity in today’s customer-centric market. IoB enables companies to deliver hyper-relevant messages and offers at the right time, in the right context, and through the right channels.

By continuously monitoring and analyzing consumer behavior, IoB enables businesses to stay ahead of shifting trends and adapt their strategies in real-time. This dynamic approach not only enhances the consumer experience but also builds brand loyalty, as customers feel understood and valued. Furthermore, IoB-driven insights allow for more precise segmentation, ensuring that marketing efforts are well-spent on the appropriate audiences. Ultimately, the integration of IoB in personalization and targeting processes empowers businesses to maximize their ROI and foster long-term relationships with their customers.

The Power of Contextual Targeting

Context is crucial for personalization. With access to data from multiple sources like websites, social media, and location-based services, IoB provides a comprehensive view of customers. This enables businesses to understand not just what consumers are doing, but why. By leveraging this data, companies can tailor their messaging and offers to fit a user’s current situation, needs, and preferences. For instance, a retail brand can use IoB to send personalized promotions to shoppers who have shown interest in specific products. Contextual targeting helps businesses refine their customer journey maps, identifying pain points and optimizing interactions for a seamless experience. This leads to improved customer satisfaction, reduced friction, and a more cohesive brand experience, ultimately driving loyalty and long-term success.

Enhanced User Experience through Personalization

IOB User Experience

One of the most significant benefits of IoB in personalization is the ability to deliver tailored content and experiences. By understanding individual user behaviors, businesses can provide recommendations, offers, and content that align with each user’s interests. For example, e-commerce platforms like ShopEase leverage IoB to create seamless shopping journeys. ShopEase collects data from various touchpoints, constructing comprehensive profiles for each user. This enables the platform to personalize product suggestions, driving higher sales and customer satisfaction. Moreover, IoB extends to customer support, where virtual assistants and chatbots use behavioral data to anticipate needs and provide timely responses, enhancing overall user experience.

The Ethical Implications of IoB in Personalization

While IoB offers vast benefits in personalization, it also presents ethical considerations. Companies must responsibly and transparently handle sensitive data, ensuring explicit user consent and robust privacy measures. Ethical practices are essential to maintain consumer trust as IoB evolves. Moreover, businesses must address potential algorithmic biases in IoB-driven personalization, which could reinforce stereotypes or exclude users. Regular audits, diverse development teams, and transparency in data use can help mitigate these risks. By prioritizing these measures, businesses can ensure their IoB strategies are both effective and equitable for all users.

Precision in Marketing Efforts

IOB Marketing Efforts

IoB enables precise targeting by allowing businesses to segment their audience based on behavior, complementing traditional demographic-based targeting with behavioral data. This comprehensive understanding leads to more effective marketing campaigns, as tailored messages and offers resonate with specific user segments. For instance, CMOs can use IoB data to identify high-value customers and create targeted campaigns that yield higher ROI.

By leveraging IoB data, businesses can also employ real-time marketing strategies that adjust based on current customer behaviors and conditions. This dynamic approach ensures the relevance and timeliness of marketing messages. For example, a travel agency could send personalized destination recommendations based on recent travel searches, while retailers might push real-time discounts to nearby customers to drive immediate foot traffic. This precision and responsiveness not only enhance customer engagement but also improve the effectiveness of marketing efforts, increasing conversions and fostering customer loyalty.

Improved Customer Retention

IOB Customer Retention

Understanding customer behavior is key to retention. IoB allows businesses to anticipate customer needs and proactively address potential issues. By analyzing patterns in user behavior, companies can identify signs of churn and implement retention strategies. For example, subscription-based services can use IoB to detect when a user is likely to cancel and offer personalized incentives to retain them. This proactive approach not only reduces churn but also strengthens customer loyalty. By leveraging IoB-driven insights, companies can implement more tailored and timely interventions that resonate with their customers on a personal level.

Integration with Behavioral Analytics

Our previous discussion on IoB in behavioral analytics highlighted the importance of understanding user behavior to drive business decisions. When combined with personalization and targeting, IoB provides a comprehensive framework for optimizing customer interactions. Behavioral analytics offers insights into why users behave a certain way, while IoB focuses on leveraging these behaviors for targeted actions. This synergy enhances the effectiveness of both personalization and targeting strategies, creating a seamless customer experience. By combining the strengths of IoB and behavioral analytics, businesses can create highly adaptive and responsive customer engagement models. This integration allows for continuous learning and adjustment based on real-time data, ensuring that marketing efforts remain pertinent and effective.

Cons

Collecting and analyzing behavioral data raises significant privacy concerns that need to be addressed to maintain user trust. Ensuring the security of sensitive user data is paramount to protect against breaches and misuse. The implementation complexity of integrating IoB into existing systems can be both resource-intensive and challenging, requiring substantial investment in time and technology. Moreover, the effectiveness of IoB is highly dependent on the quality and accuracy of the data collected; poor data quality can lead to ineffective or misleading insights. Finally, adhering to data protection regulations is crucial for compliance, as failure to do so can result in legal repercussions and diminished consumer confidence.

The Future of IoB in Personalization and Targeting

IOB Future of IoB in Personalization and Targeting

Looking ahead, the future of IoB in personalization and targeting is promising yet challenging. As technology continues to advance, the potential for even more granular and real-time personalization will grow. However, businesses must navigate privacy concerns and regulatory landscapes carefully. The integration of IoB with emerging technologies like artificial intelligence and machine learning will further enhance its capabilities, providing deeper insights and more precise targeting. Companies that invest in robust IoB strategies will be well-positioned to thrive in the competitive digital marketplace. Overall, IoB is transforming the way businesses interact with their customers and will continue to shape the future of personalization and targeting in the years to come. So, it is essential for companies to embrace this technology and put ethical frameworks in place to ensure responsible use of user data for a seamless and personalized customer experience.

Conclusion

The Internet of Behaviors (IoB) represents a revolutionary way to understand and influence user behavior through data. Throughout this blog series, we’ve explored various aspects of IoB, from smart cities to behavioral analytics, and its impact on personalization and targeting. It’s clear that IoB has the potential to transform customer interactions, urban management, and business strategies. However, businesses must implement ethical practices and robust data protection measures to build trust. Leveraging behavioral data enables companies to deliver tailored experiences, driving engagement, conversions, and retention. While promising, IoB also presents challenges that need careful navigation. Tech executives, CMOs, and business owners must embrace IoB to stay competitive and succeed in a more personalized future.

IoB: Harness the Power of the Internet of Behaviors to Enhance Consumer Insights

IOB Data Overload

In our previous blog, we delved into the transformative potential of IoB in the context of smart cities. We explored how integrating IoB technologies can optimize urban living by enhancing public services, improving traffic management, and promoting sustainable practices. By collecting and analyzing data from a myriad of connected devices, city planners can gain invaluable insights into residents’ behaviors and preferences, thus creating more responsive and efficient urban environments.

In the fast-paced digital age, understanding human behavior has become more crucial than ever for businesses and organizations looking to stay competitive. Enter the Internet of Behaviors (IoB)—a powerful extension of the Internet of Things (IoT) that promises to revolutionize behavioral analytics. By collecting and analyzing data from a multitude of sources, including social media interactions, digital platforms, and IoT devices, IoB offers unprecedented insights into human behavior. This blog explores the profound effects of IoB in behavioral analytics, highlighting its benefits, cons, and future potential while emphasizing the importance of ethical implementation.

The Benefits of IoB in Behavioral Analytics

IOB Customer experience

Enhanced Customer Experience

One of the most compelling benefits of IoB in behavioral analytics is its ability to tailor customer experiences. Businesses can gain a 360-degree view of their customers by leveraging data from various touch points. This holistic perspective enables companies to deliver personalized experiences that resonate with individual preferences and needs. For instance, retail companies can use IoB to understand shopping behaviors and preferences, allowing them to create personalized marketing campaigns, product recommendations, and loyalty programs that significantly enhance customer satisfaction and engagement. This not only boosts customer loyalty but also improves the likelihood of repeat purchases and positive word-of-mouth recommendations.

Improved Decision-Making

IoB doesn’t just collect data; it transforms it into actionable insights. For CEOs and CTOs, this means making more informed decisions based on real-time data analysis. By identifying patterns, trends, and correlations in behavior, IoB helps organizations anticipate customer needs, optimize operations, and seize new business opportunities. In the healthcare industry, for example, IoB can analyze patient behavior to predict health trends and improve preventative care strategies, ultimately leading to better patient outcomes and reduced healthcare costs. In essence, IoB enables businesses to stay ahead of the curve and make data-driven decisions that drive success.

Risk Management and Fraud Prevention

IOB Risk and Fraud Management

For businesses, understanding and mitigating risks is paramount. IoB can play a pivotal role in identifying potential risks and preventing fraud. By analyzing behavioral data, organizations can detect anomalies and suspicious activities that might indicate fraudulent actions. In the financial sector, this could mean monitoring transaction patterns to prevent identity theft and financial fraud, thus safeguarding both the institution and its customers. In a world where cybercrime is on the rise, IoB offers significant potential in mitigating risks and protecting sensitive data. Enhanced Marketing Strategies

The fusion of IoB with marketing analytics opens new horizons for CMOs. With detailed insights into consumer behavior, marketers can fine-tune their strategies to target the right audience with the right message at the right time. This level of precision not only maximizes marketing ROI but also builds stronger customer relationships. For instance, a CMO could use IoB data to create hyper-targeted advertising campaigns that resonate with specific customer segments, leading to higher conversion rates and brand loyalty. By combining IoB with marketing analytics, businesses can gain a competitive edge and drive growth.

Operational Efficiency

Engineers and business owners can benefit from the operational efficiencies brought about by IoB. By analyzing data from IoT devices and digital platforms, companies can identify bottlenecks, streamline processes, and optimize resource allocation. This, in turn, enhances productivity and reduces operational costs. In the manufacturing industry, IoB can monitor equipment performance and predict maintenance needs, minimizing downtime and ensuring smooth operations. As IoB continues to evolve, it has the potential to revolutionize supply chain management by providing real-time visibility and insights into the movement of goods. Ultimately, IoB can improve overall operational efficiency by enabling businesses to make data-driven decisions that optimize processes and resources.

The Cons of IoB in Behavioral Analytics

IOB Operational Efficiency

Privacy Concerns

While the benefits of IoB are undeniable, it also raises significant privacy concerns. The extensive collection and analysis of personal data can lead to potential misuse or unauthorized access. Businesses must ensure they adopt stringent data protection measures to safeguard user information. Transparency and consent are key—customers should be fully aware of how their data is being used and have the option to opt out if they choose. Additionally, government regulations must be put in place to prevent the misuse of data and protect individuals’ privacy rights.

Ethical Dilemmas

The ethical implications of IoB cannot be overlooked. The line between insightful data analysis and invasive surveillance can sometimes blur. It’s crucial for businesses to implement IoB ethically, respecting user privacy and avoiding manipulative practices. This includes adhering to ethical guidelines, conducting regular audits, and fostering an organizational culture that prioritizes ethical considerations in data usage. Responsible and ethical implementation of IoB is essential to maintain trust and credibility with customers.

Data Accuracy and Reliability

IOB Privacy Concerns

The effectiveness of IoB hinges on the accuracy and reliability of the data collected. Inaccurate or incomplete data can lead to misguided insights and decisions. Businesses must invest in robust data validation processes and employ advanced analytics techniques to ensure data integrity. Additionally, continuous monitoring and updating of data sources are essential to maintain the relevance and accuracy of behavioral analytics. Failure to do so can result in flawed insights and hinder the potential benefits of IoB.

Ensuring data integrity also involves addressing potential biases in data collection and analysis. Biases can skew results and reinforce existing prejudices, leading to unfair treatment of certain groups. As such, businesses must actively seek to identify and mitigate biases in their IoB systems. This may include diversifying data sources, employing algorithms designed to detect and correct biases, and continuously reevaluating data collection methods. 

High Implementation Costs

Implementing IoB can be a costly endeavor, especially for small and medium-sized enterprises. The integration of IoT devices, data analytics platforms, and skilled personnel requires substantial investment. However, the long-term benefits often outweigh the initial costs, making it a worthwhile investment for businesses aiming to stay competitive in the digital landscape. As technology continues to advance, the costs associated with IoB implementation are expected to decrease, making it more accessible and feasible for smaller businesses.

Potential for Data Overload

With the vast amount of data generated by IoB, there’s a risk of data overload. Businesses may struggle to process and analyze the sheer volume of information effectively. To mitigate this, organizations should adopt sophisticated data management solutions and employ data scientists capable of extracting meaningful insights from large datasets. It’s crucial to strike a balance between the quantity and quality of data for optimal results. Additionally, businesses should only collect relevant data and avoid collecting unnecessary or sensitive information. This not only helps prevent data overload but also addresses privacy concerns mentioned earlier.

The Future of IoB in Behavioral Analytics

IOB Improved Decision-Making

The future of IoB in behavioral analytics holds immense potential. As technology continues to advance, we can expect even more sophisticated data collection and analysis techniques. The integration of artificial intelligence (AI) and machine learning (ML) will further enhance the capabilities of IoB, enabling more accurate predictions and deeper insights into human behavior.

In the coming years, we may see IoB being leveraged across various sectors, from public policy and urban planning to education and entertainment. Governments could use IoB to design more effective public policies by understanding citizen behavior and preferences. Educational institutions could personalize learning experiences based on student behavior and engagement patterns, leading to improved learning outcomes.

Conclusion

The Internet of Behaviors (IoB) represents a transformative force in the realm of behavioral analytics. By analyzing and interpreting human behaviors through data from diverse sources, IoB offers businesses valuable insights that drive efficiency, informed decision-making, and enhanced customer experiences. However, to reap the benefits of IoB, it is essential to address privacy concerns, ethical dilemmas, and data accuracy issues.

As we look to the future, the integration of AI, ML, and other emerging technologies will further amplify the impact of IoB, opening new avenues for innovation and growth. By adopting an ethical approach to data protection and transparency, businesses can harness the power of IoB to create a positive social impact while gaining a competitive edge. So, while IoB may pose risks and challenges, it also presents immense opportunities for businesses to thrive in the digital age. Stay tuned for our next blog post, where we will explore the role of IoB in personalization and targeting, and how it can revolutionize marketing strategies and customer engagement.

Smart Cities: Transforming Urban Living for a Sustainable Future

Smart City

The Internet of Behaviors (IoB) is transforming how we interact with technology and data. By leveraging insights from user behaviors, IoB aims to enhance user experiences, streamline operations, and drive innovation across various sectors. Among its most promising applications is within the realm of smart cities. IoB smart cities are designed to create more efficient, sustainable, and livable urban environments by integrating IoT devices, data analytics, and behavioral insights. In this blog, we’ll delve into what makes IoB smart cities a blueprint for the future. 

The Rise of Smart Cities

The concept of smart cities revolves around creating environments that are not only technologically advanced but also focused on improving the everyday experiences of their inhabitants. At the core, smart cities utilize a network of interconnected devices and systems—often referred to as the Internet of Things (IoT) —to gather real-time data. This extensive data collection enables city planners and administrators to make informed decisions on urban planning and management.

For instance, smart transportation systems can reduce traffic congestion and improve public transit efficiency by analyzing patterns and predicting travel demands. Similarly, smart grids help optimize energy consumption, leading to more sustainable power usage and reduced environmental impact. Waste management systems benefit from sensors that monitor bin levels and dynamically adjust collection routes, ensuring efficient resource use and cleaner urban spaces. Public services such as street lighting, emergency response, and even healthcare are enhanced through data-driven approaches that adapt to the needs of residents.

Overall, the vision of a smart city is to seamlessly integrate technology and data into the urban fabric, creating a responsive, adaptive, and holistic environment that prioritizes the well-being of its citizens while managing resources judiciously.

The Importance of IoB Smart Cities

Internet Of Behaviors

The importance of IoB smart cities cannot be overstated. They represent a critical step towards creating urban environments that are not only more efficient and sustainable but also more responsive to the needs and behaviors of their inhabitants. By harnessing the power of data, IoB smart cities can optimize resource allocation, enhance public services, and foster economic growth, ultimately improving the quality of life for their residents. As we continue to explore the potential of IoB, smart cities will undoubtedly play a significant role in shaping our future. So, it is crucial to monitor and regulate their development carefully. IoB smart cities can pave the way toward a smarter, more connected, and sustainable future with proper planning and consideration for ethical and privacy concerns. 

As we continue to innovate and expand our understanding of IoB, the potential for smart cities will only continue to grow. By embracing the principles of sustainability, efficiency, and citizen-centric design, IoB smart cities have the power to create a better world for all. With careful planning and consideration for ethical and privacy concerns, these cities can pave the way toward a smarter, more connected, and sustainable future.

Benefits of IoB Smart Cities

One of the primary advantages of IoB smart cities is their contribution to sustainability and the environment. Utilizing green energy solutions such as solar panels and wind turbines, these cities can significantly reduce their carbon footprint. Additionally, advanced waste management systems powered by IoB technologies enable efficient sorting and recycling processes, leading to reduced landfill usage. Air quality monitoring devices provide real-time data, helping to mitigate pollution and protect public health. Water conservation efforts are also enhanced through smart metering and leak detection technologies, ensuring sustainable water usage. Overall, IoB smart cities promote sustainable living and contribute to a healthier environment.

Urban Mobility

IOB Smart City

Urban mobility is another area where IoB smart cities excel. Autonomous vehicles, guided by IoB data, promise to reduce traffic congestion and lower accident rates, offering a safer and more efficient mode of transport. Innovations in public transport include real-time scheduling and route optimization based on passenger behavior and preferences. Bike-sharing programs, powered by IoB, provide a flexible and eco-friendly alternative to traditional transportation methods. Advanced traffic management systems use data analytics to adjust traffic signals dynamically, reducing wait times and improving overall traffic flow. These advancements contribute to a more streamlined and efficient urban mobility experience.

Public Safety and Security

Smart Governance

Public safety and security are paramount in IoB smart cities. Modern surveillance systems equipped with facial recognition and behavior analysis can preemptively identify and address potential security threats. Emergency response technologies, such as connected fire alarms and medical alert systems, ensure rapid assistance during crises. Cybersecurity measures are crucial to protect the vast amounts of data generated and stored within IoB ecosystems, safeguarding both infrastructure and citizen information from malicious attacks. Through these technological advancements, IoB smart cities create a safer and more secure environment for their citizens.

Healthcare

In terms of healthcare and well-being, IoB plays a transformative role. Telemedicine services allow for remote consultations, making healthcare more accessible, especially in underserved areas. Smart hospitals utilize IoB technologies for patient monitoring, resource management, and operational efficiency, improving the overall standard of care. Wearable health monitoring systems enable individuals to track their vital signs and receive personalized health advice. Public health data collected through IoB devices aid in the early detection and management of disease outbreaks, promoting a healthier community. These advancements in healthcare and well-being, powered by IoB, contribute to a better quality of life for citizens.

Smart Governance

iOB governance

Smart governance is another cornerstone of IoB smart cities. E-governance platforms facilitate seamless interaction between citizens and government bodies, improving service delivery and citizen satisfaction. Data-driven decision-making ensures that policies and initiatives are based on accurate and timely information, enhancing their efficacy. Citizen services, such as online portals for utilities and permits, simplify processes and reduce administrative burdens. Open data initiatives enable citizens to access and analyze government data, fostering transparency and accountability. Through these digital advancements, IoB smart cities promote efficient, transparent, and responsive governance.

Connectivity in IoB Communities

Smart City Grid

Communities within IoB smart cities are connected through a seamless network of IoT devices and data platforms. This interconnectedness enables real-time communication and collaboration across various sectors. For example, smart grids dynamically balance energy supply and demand, while smart street lighting adjusts based on pedestrian and vehicular traffic patterns. Public transport systems communicate with traffic management centers to optimize routes and schedules, ensuring efficient and reliable service. These connected communities also foster citizen engagement and participation through social media platforms and community forums, allowing for input and feedback on various initiatives. The connectivity in IoB communities promotes a sense of belonging and enables collaboration towards shared goals, ultimately creating a more cohesive society.

Furthermore, IoB technologies facilitate community engagement. Residents can provide feedback and report issues through mobile apps, contributing to continuous improvement and fostering a sense of ownership and participation. Social media platforms and online forums enable the sharing of experiences and ideas, strengthening community bonds.

Cons of IoB Smart Cities

Despite their numerous benefits, IoB smart cities have challenges. The reliance on extensive data collection raises significant privacy concerns. Ensuring that personal information is securely stored and ethically used is paramount to maintaining public trust. Additionally, the high cost of implementation and maintenance can be a barrier for some municipalities. Integrating diverse technologies requires substantial investment in infrastructure and ongoing operational costs. 

There is also the risk of technological obsolescence. As new technologies emerge, existing systems may become outdated quickly, necessitating continuous upgrades and investments. Interoperability issues arise when integrating multiple IoT devices and platforms, potentially leading to inefficiencies and increased complexity. Finally, the need for standardization and regulations for IoB technologies can create compliance challenges and hinder widespread adoption. Policymakers and industry leaders need to address these concerns and establish guidelines to ensure the responsible implementation of IoB in smart cities.

The Future of IoB Smart Cities

Machine Learning

Looking ahead, the potential of IoB smart cities is immense. Future developments may include even more sophisticated AI and machine learning algorithms capable of predicting and responding to urban challenges with unprecedented accuracy. Enhanced connectivity through 5G networks will provide faster and more reliable communication between devices, enabling more complex and integrated solutions. As the IoB ecosystem continues to expand, it will also create new job opportunities in fields such as data science and cyber security. However, careful consideration must be given to data privacy and security as these technologies continue to evolve. As technology continues to shape the world around us, IoB smart cities will play a crucial role in how we design and manage our urban environments. By leveraging the power of data, connectivity, and citizen engagement, these cities have the potential to become more sustainable, efficient, and responsive

We can also expect advancements in autonomous systems, from self-driving cars to drone-based delivery services, further revolutionizing urban mobility and logistics. The integration of virtual and augmented reality technologies may offer new ways for citizens to interact with their environment, from virtual city tours to augmented reality navigation aids. The possibilities are endless, and as we continue to push the boundaries of what is possible with IoB, smart cities will continue to evolve and shape the world around us. Municipalities, policymakers, and industry leaders need to work together to ensure the responsible and ethical development of IoB smart cities for the betterment of society as a whole. With careful planning, collaboration, and consideration for all stakeholders, we can create a future where technology enhances our lives and makes our cities smarter, more connected, and more sustainable than ever before.

Conclusion

IoB smart cities represent a promising vision for the future of urban living. By integrating IoT devices, data analytics, and behavioral insights, these cities can achieve greater efficiency, sustainability, and quality of life for their residents. However, addressing privacy, cost, and technological obsolescence challenges is crucial for realizing their full potential.

As we continue to explore the possibilities of IoB, the next frontier lies in its application to behavioral analysis, which will be the focus of our upcoming blog. In our next blog, we will dive deeper into how IoB revolutionizes behavioral analysis, offering new insights into human behavior and driving innovations across various sectors.

How Zigbee Pro Makes Life Easier for IoT Developers

The IoT has proliferated our everyday lives in a growing variety of ways. In 2021, there were more than 10 billion active IoT devices. That number is expected to grow past 25.4 billion by 2030. IoT solutions will generate $4-11 trillion in economic value by 2025.

Hundreds of manufacturers create IoT devices of all varieties—interoperability is necessity. In order to facilitate this, IoT developers generally adhere to a communications protocol known as Zigbee Pro.

WHAT IS ZIGBEE PRO?

 

Zigbee Pro is a low power, low data rate Wireless Personal Area Network (WPAN) protocol which streamlines device connections. The goal of the protocol is to deliver a single communications standard that simplifies the nauseating array of proprietary APIs and wireless technologies used by IoT manufacturers.

Zigbee Pro is the latest in a line of protocols. The certification process is facilitated by the Zigbee Alliance—now commonly known as the Connectivity Standards Alliance—which formed in 2002. The Connectivity Standards developed the first version of Zigbee in 2004 and gradually rolled out improved versions until the most current version in 2014.

HOW DOES IT WORK?

Zigbee is composed of a number of layers that form a protocol stack. Each layer contributes functionality to the ones below it, making it easier for developers to deploy these functions without explicitly having to write them. The layers include a radio communication layer based on the IEEE standard 802.15.4, a network layer (Zigbee Pro), the application layer known as Dotdot, and the certification layer which is compliant with the Connectivity Standards Alliance.

One of the focuses of the Zigbee standard is to deliver low-power requirements. Battery powered devices must have a 2 year battery life in order to be certified.

ZIGBEE DEVICES

Mesh networking enables Zigbee networks to operate more consistently than WiFi and Bluetooth. Each device on the network becomes a repeater, which ensures that losing one device won’t affect the other devices in the mesh.

There are three classes of Zigbee devices:

Zigbee Coordinator – The coordinator forms the root of the network tree, storing information about the network and functioning as a repository for security keys. This is generally the hub, bridge, or smart home controller—such as the app from which you control your smart home.

Zigbee Router – The router can run application functions as well as act as an intermediate router to pass data on to other devices. The router is generally a typical IoT device, such as a powered lightbulb.

Zigbee End Device – This is the simplest type of device—requiring the least power and memory to perform the most basic functions. It cannot relay data and its simplicity enables it to be asleep the majority of the time. An example of an end device would be a smart switch or a sensor that only sends a notification when a specific event occurs.

The Zigbee Pro protocol has become the gold standard for IoT developers. Many commercial IoT apps and smart home controllers function under the Zigbee Pro protocol. Examples include: Samsung SmartThings Hub, Amazon Echo, and the Philips Hue Bridge.

How the Internet of Behaviors Will Shape the Future of Digital Marketing

In the digital age, businesses need to leverage every possible platform and cutting-edge technology in order to get a leg up on the competition. We’ve covered the Internet of Things extensively on the Mystic Media blog, but a new and related tech trend is making waves. This trend is called the Internet of Behaviors and according to Gartner, about 40% of people will have their behavior tracked by the IoB globally by 2023.

WHAT IS THE IOB?

Internet of Behavior, or the IoB, exists at the intersection of technology, data analytics, and behavioral science. The IoB leverages data collected from a variety of sources, including online activities, social media, wearable devices, commercial transactions and IoT devices, in order to deliver insights related to consumers and purchasing behavior.

With devices more interconnected than ever, the IoB tracks, gathers, combines and interprets massive data sets so that businesses can better understand their consumers. Businesses leverage analysis from the IoB to offer more personalized marketing with the goal of influencing consumer decision making.

HOW DOES IT WORK?

Traditionally, a car insurance company would analyze a customer’s driving history in order to determine if they are a good or bad driver. However, in today’s digital age, they might take it a step further and analyze social media profiles in order to “predict” whether a customer is a safe driver. Imagine what insights they could gather from a user’s Google search history or Amazon purchases? Access to large datasets enables large companies to create psychographic profiles and gather an enhanced understanding of their customer base.

Businesses can use the IoB for more than just purchasing decisions. UX designers can leverage insights to deliver more effective customer experiences. Large companies such as Ford are designing autonomous vehicles that change based on the city, modulating behavior based on vehicle traffic, pedestrians, bicycles and more.

GBKSOFT created a mobile application that collects data from wearable devices in order to help golfers improve their skills. The application records each golf ball hit, including the stroke, force, trajectory and angle, and delivers visual recommendations to improve their swing and technique. Insights gathered through data are translated into behavioral trends that are then converted into recommendations to improve the user’s game.

The IoB is all about collecting data that can be translated into behavior which helps companies understand consumer tendencies and translate them into meaningful actions.

CONCERNS

While there is quite a bit of enthusiasm surrounding the potential impact of the IoB for B2C companies, a number of legal concerns come with it. A New York Times article, written by Harvard Business School emeritus professor Shoshana Zuboff, warns of the age of surveillance capitalism where tech behemoths surveil humans with the intent to control their behavior.

Due to the speed at which technology and the ability to collect data has proliferated, privacy and data security are under-regulated and major concerns for consumers. For example, Facebook was applying facial recognition scans in advance of the 2016 election without user’s consent. Cambridge Analytica’s use of psychoanalytic profiles has been the subject of much derision. Momentum for data privacy regulation is growing and since the IoB hinges on the ability for companies to collect and market data, forthcoming regulations could inhibit its impact.

CONCLUSION

Despite regulatory concerns, the IoB is a sector that we expect to see grow over time. As the IoT generates big data and AI evolves to learn how to parse through and analyze it, it’s only natural that companies will take the next step to leverage analysis to enhance their understanding of their customers’ behaviors and use it to their advantage. The IoB is where that next step will take place.

How Bluetooth Became the Gold Standard of Wireless Audio Technology

Bluetooth technology has established itself over the years as the premiere wireless audio technology and a staple of every smartphone user’s daily mobile experience. From wireless headphones, to speakers, to keyboards, gaming controllers, IoT devices, and instant hotspots—Bluetooth is used for a growing variety of functions every year.

While Bluetooth is now a household name, the path to popularity was built over the course of over 20 years.

CONCEPTION

In 1994, Dr. Jaap Haartsen—an electrical engineer working for Ericsson’s Mobile Terminal Division in Lund—was tasked with creating an indoor wireless communication system for short-range radio connections. He ultimately created the Bluetooth protocol. Named after the renowned Viking king who united Denmark and Norway in 958 AD, the Bluetooth protocol was designed to replace RS-232 telecommunication cables using short range UHF radio waves between 2.4 and 2.485 GHz.

In 1998, he helped create the Bluetooth Special Interest Group, driving the standardization of the Bluetooth radio interface and obtaining worldwide regulatory approval for Bluetooth technology. To this day, Bluetooth SIG publishes and promotes the Bluetooth standard as well as revisions.

BLUETOOTH REACHES CONSUMERS

In 1999, Ericsson introduced the first major Bluetooth product for consumers in the form of a hands-free mobile headset. The headset won the “Best of Show Technology” award at COMDEX and was equipped with Bluetooth 1.0.

Each iteration of Bluetooth has three main distinguishing factors:

  • Range
  • Data speed
  • Power consumption

The strength of these factors is determined by both the modulation scheme and data packet employed. As you might imagine, Bluetooth 1.0 was far slower than the Bluetooth we’ve become accustomed to in 2021. Data speeds capped at 1Mbps with a range up to 10 meters. While we use Bluetooth to listen to audio on a regular basis today, it was hardly equipped to handle music and primarily designed for wireless voice calls.

THE BLUETOOTH EVOLUTION

The Bluetooth we currently enjoy in 2021 is version 5. Over the years, Bluetooth’s range, data speed, and power consumption have increased dramatically.

In 2004, Bluetooth 2.0 focused on enhancing the data rate, pushing from 0.7Mbps in version 1 to 1-3Mbps while increasing range from 10m to 30m. Bluetooth 3.0 increased speeds in 2009, allowing up to 24Mbps.

In 2011, Bluetooth 4.0 introduced a major innovation in BLE (Bluetooth Low Energy). BLE is an alternate Bluetooth segment designed for very low power operation. It enables major flexibility to build products that meet the unique connectivity requirements of their market. BLE is tailored toward burst-like communications, remaining in sleep mode before and after the connection initiates. The decreased power consumption takes IoT devices like industrial monitoring sensors, blood pressure monitoring, and Fitbit devices to the next level. These devices can employ BLE to run at 1Mbps at very low power consumption rates. In addition to lowering the power consumption, Bluetooth 4.0 doubles the typical maximum range from 30m in Bluetooth 3.0 to 60m.

BLUETOOTH 5

Bluetooth 5 is the latest version of the technology. Bluetooth 5 doubles the bandwidth by doubling the speed of transmission. In addition, it quadruples the typical max range, bringing it up to 240m. Bluetooth 5 also introduces Bluetooth Low Energy audio, which enables one device to share audio with multiple other devices.

CONCLUSION

Bluetooth is a game-changing technology which stands to revolutionize more than just audio. IoT devices, health tech, and more stand to improve as the Bluetooth SIG continues to upgrade the protocol. After thirty years of improvement, the possibilities remain vast for savvy developers to take advantage of the latest Bluetooth protocols to build futuristic wireless technologies.

Cloud-Powered Microdroid Expands Possibilities for Android App Developers

Android developers have a lot to look forward to in 2021, 2022, and beyond. Blockchain may decentralize how Android apps are developed, Flutter will see increased adoption for cross-platform development, and we expect big strides in AR and VR for the platform. Among the top trends in Android development, one potential innovation has caught the attention of savvy app developers: Microdroid.

Android developers and blogs were astir earlier this year when Google engineer Jiyong Park announced via the Android Open Source Project that they are working on a new, minimal Android-based Linux image called Microdroid.

Details about the project are scant, but it’s widely believed that Microdroid will essentially be a lighter version of the Android system image designed to function on virtual machines. Google is preparing for a world in which even smartphone OS’s require a stripped-down version that can be run through the cloud.

Working from a truncated Linux, Microdroid will pull the system image from the device (tablet or phone), creating a simulated environment accessible from any remote device. It has the ability to enable a world in which users can access Google Play and any Android app using any device.

What does this mean for developers?

Microdroid will open up new possibilities for Android apps in embedded and IoT spaces which require potentially automated management and a contained virtual machine which can mitigate security risks. Cloud gaming, cloud computing—even smartphones with all features stored in the cloudare possible. Although we will have to wait and see what big plans Google has for Microdroid and how Android developers capitalize on it, at this juncture, it’s looking like the shift to the cloud may entail major changes in how we interact with our devices. App developers are keen to keep their eyes and heads in the cloud.

Although no timeline for release has been revealed yet, we expect more on Microdroid with the announcement of Android 12.

LiDAR: The Next Revolutionary Technology and What You Need to Know

In an era of rapid technological growth, certain technologies, such as artificial intelligence and the internet of things, have received mass adoption and become household names. One up-and-coming technology that has the potential to reach that level of adoption is LiDAR.

WHAT IS LIDAR?

LiDAR, or light detection and ranging, is a popular remote sensing method for measuring the exact distance of an object on the earth’s surface. Initially used in the 1960s, LiDAR has gradually received increasing adoption, particularly after the creation of GPS in the 1980s. It became a common technology for deriving precise geospatial measurements.

LiDAR requires three components: the scanner, laser, and GPS receiver. The scanner sends a pulsed laser to the GPS receiver to calculate an object’s variable distances from the earth surface. The laser emits light which travels to the ground and reflects off things like buildings, tree branches and more. The reflected light energy then returns to the LiDAR sensor where the associated information is recorded. In combination with photodetector and optics, it allows for an ultra-precise distance detection and topographical data.

WHY IS LIDAR IMPORTANT?

As we covered in our rundown of the iPhone 12, new iOS devices come equipped with a brand new LiDAR scanner. LiDAR now enters the hands of consumers who have Apple’s new generation of devices, enabling enhanced functionality and major opportunities for app developers. The proliferation of LiDAR signals toward the technology finding mass adoption and household name status.

There are two different types of LiDAR systems: Terrestrial and Airborne. Airborne LiDAR are installed on drones or helicopters for deriving an exact measurement of distance, while Terrestrial LiDAR systems are installed on moving vehicles to collect pinpoints. Terrestrial LiDAR systems are often used to monitor highways and have been employed by autonomous cars for years, while airborne LiDAR are commonly used in environmental applications and gathering topographical data.

With the future in mind, here are the top LiDAR trends to look out for moving forward:

SUPERCHARGING APPLE DEVICES

LiDAR enhances the camera on Apple devices significantly. Auto-focus is quicker and more effective on those devices. Moreover, it supercharges AR applications by greatly enhancing the speed and quality of a camera’s ability to track the location of people as well as place objects.

One of the major apps that received a functionality boost from LiDAR is Apple’s free Measure app, which can measure distance, dimensions, and even whether an object is level. The measurements determined by the app are significantly more accurate with the new LiDAR scanner, capable of replacing physical rulers, tape measures, and spirit levels.

Microsoft’s Seeing AI application is designed for the visually impaired to navigate their environment, however, LiDAR takes it to the next level. In conjunction with artificial intelligence, LiDAR enables the application to read text, identify products and colors, and describe people, scenes, and objects that appear in the viewfinder.

BIG INVESTMENTS BY AUTOMOTIVE COMPANIES

LiDAR plays a major role in autonomous vehicles, relying on a terrestrial LiDAR system to help them self-navigate. In 2018, reports suggest that the automotive segment acquired a business share of 90 percent. With self-driving cars inching toward mass adoption, expect to see major investments in LiDAR by automotive companies in 2021 and beyond.

As automotive companies look to make major investments in LiDAR, including Volkswagen’s recent investment in Aeva, many LiDAR companies are competing to create the go-to LiDAR system for automotive companies. Check out this great article by Wired detailing the potential for this bubble to burst.

LIDAR DRIVING ENVIRONMENTAL APPLICATIONS

Beyond commercial applications and the automotive industry, LiDAR is gradually seeing increased adoption for geoscience applications. The environmental segment of the LiDAR market is anticipated to grow at a CAGR of 32% through 2025. LiDAR is vital to geoscience applications for creating accurate and high-quality 3D data to study ecosystems of various wildlife species.

One of the main environmental uses of LiDAR is for soliciting topographic information on landscapes. Topographic LiDAR is expected to see a growth rate of over 25% over the coming years. These systems can see through forest canopy to produce accurate 3D models of landscapes necessary to create contours, digital terrain models, digital surface models and more.

CONCLUSION

In March 2020, after the first LiDAR scanner became available in the iPad Pro, The Verge put it perfectly when they said that the new LiDAR sensor is an AR hardware solution in search of software. While LiDAR has gradually found increasing usage, it is still a powerful new technology with burgeoning commercial usage. Enterprising app developers are looking for new ways to use it to empower consumers and businesses alike.

For supplementary viewing on the inner workings of the technology, check out this great introduction below, courtesy of Neon Science.

How AI Fuels a Game-Changing Technology in Geospatial 2.0

Geospatial technology describes a broad range of modern tools which enable the geographic mapping and analysis of Earth and human societies. Since the 19th century, geospatial technology has evolved as aerial photography and eventually satellite imaging revolutionized cartography and mapmaking.

Contemporary society now employs geospatial technology in a vast array of applications, from commercial satellite imaging, to GPS, to Geographic Information Systems (GIS) and Internet Mapping Technologies like Google Earth. The geospatial analytics market is currently valued between $35 and $40 billion with the market projected to hit $86 billion by 2023.

GEOSPATIAL 1.0 VS. 2.0

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Geospatial technology has been in phase 1.0 for centuries; however, the boon of artificial intelligence and the IoT has made Geospatial 2.0 a reality. Geospatial 1.0 offers valuable information for analysts to view, analyze, and download geospatial data streams. Geospatial 2.0 takes it to the next level–harnessing artificial intelligence to not only collect data, but to process, model, analyze and make decisions based on the analysis.

When empowered by artificial intelligence, geospatial 2.0 technology has the potential to revolutionize a number of verticals. Savvy application developers and government agencies in particular have rushed to the forefront of creating cutting edge solutions with the technology.

PLATFORM AS A SERVICE (PaaS) SOLUTIONS

Effective geospatial 2.0 solutions require a deep vertical-specific knowledge of client needs, which has lagged behind the technical capabilities of the platform. The bulk of currently available geospatial 2.0 technologies are offered as “one-size-fits-all” Platform as a Service (PaaS) solutions. The challenge for PaaS providers is that they need to serve a wide collection of use cases, harmonizing data from multiple sensors together while enabling users to simply understand and address the many different insights which can be gleaned from the data.

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In precision agriculture, FarmShots offers precise, frequent imagery to farmers along with meaningful analysis of field variability, damage extent, and the effects of applications through time.

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In the disaster management field, Mayday offers a centralized artificial intelligence platform with real-time disaster information. Another geospatial 2.0 application Cloud to Street uses a mix of AI and satellites to track floods in near real-time, offering extremely valuable information to both insurance companies and municipalities.

SUSTAINABILITY

The growing complexity of environmental concerns have led to a number of applications of geospatial 2.0 technology to help create a safer, more sustainable world. For example, geospatial technology can measure carbon sequestration, tree density, green cover, carbon credit & tree age. It can provide vulnerability assessment surveys in disaster-prone areas. It can also help urban planners and governments plan and implement community mapping and equitable housing. Geospatial 2.0 can analyze a confluence of factors and create actionable insight toward analyzing and honing our environmental practices.

As geospatial 1.0 models are upgraded to geospatial 2.0, expect to see more robust solutions incorporating AI-powered analytics. A survey of working professionals conducted by Geospatial World found that geospatial technology will likely make the biggest impact in the climate and environment field.

CONCLUSION

Geospatial 2.0 platforms are very expensive to employ and require quite a bit of development.  The technology offers great potential to increase revenue and efficiency for a number of verticals. In addition, it may be a key technology to help cut down our carbon footprint and create a safer, more sustainable world..

AIoT: How the Intersection of AI and IoT Will Drive Innovation for Decades to Come

We have covered the evolution of the Internet of Things (IoT) and Artificial Intelligence (AI) over the years as they have gained prominence. IoT devices collect a massive amount of data. Cisco projects by the end of 2021, IoT devices will collect over 800 zettabytes of data per year. Meanwhile, AI algorithms can parse through big data and teach themselves to analyze and identify patterns to make predictions. Both technologies enable a seemingly endless amount of applications retained a massive impact on many industry verticals.

What happens when you merge them? The result is aptly named the AIoT (Artificial Intelligence of Things) and it will take IoT devices to the next level.

WHAT IS AIOT?

AIoT is any system that integrates AI technologies with IoT infrastructure, enhancing efficiency, human-machine interactions, data management and analytics.

IoT enables devices to collect, store, and analyze big data. Device operators and field engineers typically control devices. AI enhances IoT’s existing systems, enabling them to take the next step to determine and take the appropriate action based on the analysis of the data.

By embedding AI into infrastructure components, including programs, chipsets, and edge computing, AIoT enables intelligent, connected systems to learn, self-correct and self-diagnose potential issues.

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One common example comes in the surveillance field. Surveillance camera can be used as an image sensor, sending every frame to an IoT system which analyzes the feed for certain objects. AI can analyze the frame and only send frames when it detects a specific object—significantly speeding up the process while reducing the amount of data generated since irrelevant frames are excluded.

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While AIoT will no doubt find a variety of applications across industries, the three segments we expect to see the most impact on are wearables, smart cities, and retail.

WEARABLES

Wearable-IoT-Devices

The global wearable device market is estimated to hit more than $87 billion by 2022. AI applications on wearable devices such as smartwatches pose a number of potential applications, particularly in the healthtech sector.

Researchers in Taiwan have been studying the potential for an AIoT wearable system for electrocardiogram (ECG) analysis and cardiac disease detection. The system would integrate a wearable IoT-based system with an AI platform for cardiac disease detection. The wearable collects real-time health data and stores it in a cloud where an AI algorithm detects disease with an average of 94% accuracy. Currently, Apple Watch Series 4 or later includes an ECG app which captures symptoms of irregular, rapid or skipped heartbeats.

Although this device is still in development, we expect to see more coming out of the wearables segment as 5G enables more robust cloud-based processing power, taking the pressure off the devices themselves.

SMART CITIES

We’ve previously explored the future of smart cities in our blog series A Smarter World. With cities eager to invest in improving public safety, transport, and energy efficiency, AIoT will drive innovation in the smart city space.

There are a number of potential applications for AIoT in smart cities. AIoT’s ability to analyze data and act opens up a number of possibilities for optimizing energy consumption for IoT systems. Smart streetlights and energy grids can analyze data to reduce wasted energy without inconveniencing citizens.

Some smart cities have already adopted AIoT applications in the transportation space. New Delhi, which boasts some of the worst traffic in the world, features an Intelligent Transport Management System (ITMS) which makes real-time dynamic decisions on traffic flows to accelerate traffic.

RETAIL

AIoT has the potential to enhance the retail shopping experience with digital augmentation. The same smart cameras we referenced earlier are being used to detect shoplifters. Walmart recently confirmed it has installed smart security cameras in over 1,000 stores.

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One of the big innovations for AIoT involves smart shopping carts. Grocery stores in both Canada and the United States are experimenting with high-tech shopping carts, including one from Caper which uses image recognition and built-in sensors to determine what a person puts into the shopping cart.

The potential for smart shopping carts is vast—these carts will be able to inform customers of deals and promotion, recommend products based on their buying decisions, enable them to view an itemized list of their current purchases, and incorporate indoor navigation to lead them to their desired items.

A smart shopping cart company called IMAGR recently raised $14 million in a pre-Series A funding round, pointing toward a bright future for smart shopping carts.

CONCLUSION

AIoT represents the intersection of AI, IoT, 5G, and big data. 5G enables the cloud processing power for IoT devices to employ AI algorithms to analyze big data to determine and enact action items. These technologies are all relatively young, and as they continue to grow, they will empower innovators to build a smarter future for our world.