Smart cities combine technology, government, and society to enable smart economies, mobility, a clean environment, and people living better. The Internet of Things is not a new concept. You have probably heard of smart homes and smart cars. Well, now there are smart cities. The smart home and the smart city are two major developments in IoT technology. Devices can communicate with one another, with people in homes and cities. In addition, they can even communicate with third parties from the outside. For example, a refrigerator automatically puts in a new order to a grocery store when important items like eggs, butter, or milk run low. However, there are other applications for this technology that take us beyond our homes and into the community at large. Therefore, let’s take a quick look toward the future.

As an increasing number of companies aim for comprehensive digital transformation, the need for increased connectivity and the adoption of IoT are matched only by the proliferation of cybercriminals – both the masterminds and the crime-as-a-service purchasers, whose main target is exploiting IoT devices, with their ultimate goal being attacking the entire organization. IoT devices can be compromised to leak data, harm operations, deny service, or infiltrate the organization’s IT network. Their ever-growing numbers – current stats range from 27.5 billion devices to 75 billion in only a few more years – means that secure communications and the adoption of IoT security solutions is crucial. A recent survey revealed that an average of 61 percent of businesses are using IoT to bolster operations. At the same time, 28 percent of companies experienced a cyberattack due to the use of IoT infrastructure, as threats on IoT devices tripled compared to the same period in the previous year. The data and findings are based on extensive research done in cooperation with Infiniti Research, a premier provider of market intelligence solutions for leading players across industries. As IoT devices, networks and uses are an evolving domain, organizations must keep abreast of developments in the ecosystem to take advantage of the operational and cost benefits ahead of the competition.

Imagine losing $1.5 million to fraud — that is, in fact, what an average financial fraud costs a company. In addition, the constant threat of vulnerabilities in cybersecurity is being exploited by unscrupulous hackers, which is terrifying not just for individuals but also for businesses. For companies to function smoothly without the risk of potential fraud, a robust, pre-emptive, and future-ready combat system is non-negotiable. Changing Fraud Detection With the dawn of the digital era, things have changed rapidly. But, unfortunately, while technological advancements have transformed the world around us in more ways than one, the other side of the coin is becoming uglier by the day. For example, business-related frauds have increased alarmingly, but the nature of these cases has demonstrated how smart technology can be susceptible to large-scale cyberattacks. The IoT Connected World As the Internet of Things (IoT) becomes a reality, we are now living in a more connected and integrated world than ever before. While not every industry has embraced IoT wholeheartedly, most have and are now grappling with various risks associated with potential fraud. In a bid to rapidly achieve their digital transformation goals, the security aspect has been slightly ignored by many businesses. While the IoT infrastructure offers a host of convenience, collaboration, and productivity benefits, it poses grave security threats, including direct attacks on IoT devices and IoT devices–generated data privacy issues. Even the most secure of IoT devices, networks, and systems are susceptible to malicious activity. Here are some examples of looming cybersecurity threats.

If you’ve paid a bill or made a purchase online in the past few years, you have likely noticed an increase in the number of chatbot popup windows that are available to interact with now. Unlike typing elementary phrase into Google, voice assistants like Siri or Alexa provide a more conversational interaction style. You can hold a relatively “normal” conversation with these AI bots, and they can help you perform a wide range of tasks. AI voice has been consistently gaining popularity over the past few years, and the global pandemic only accelerated its adoption. Consumers are quickly becoming comfortable with the idea of interacting with intelligent bots.  From a simple weather query to finding and booking vacation accommodations. One Statista survey predicts that the global chatbot market will reach about 1.25 billion by 2025. Chatbots and virtual assistants are becoming more popular in the workplace as well. Gartner estimates that by 2022, at least 70 percent of white-collar workers will have daily interactions with this type of AI technology. There is already a massive amount of potential for voice assistants and chatbots to improve general business operations. So it is likely that companies will want to leverage conversational AI for as many applications as possible. Chatbots are rapidly becoming more complex. There is no question that conversational AI will be an integral part of your future business strategy. For many companies, conversational AI technology is already an important factor for internal and customer-facing processes. The evolution of chatbots from simple novelties to useful assistants has happened relatively quickly. This means that businesses still have time to include AI voices into their everyday practices. However, with the rapid trajectory of chatbot evolution, it is important for companies to get on board with this trend.

Personalization and automation remain the main directions for improving the quality of the user experience. They also help make the lives of millions of people safer, more convenient, and more comfortable. Artificial intelligence (AI) and the Internet of Things (IoT) have become the main tools in recent years. It is with their help that a symbiosis of functional automation and well-tuned personalization is created. How exactly technologies affect the development of a smart home, we will analyze in the article. What is AI? Britannica AI is interpreted as the ability of a computer/robot to perform tasks set by a person. The use of artificial intelligence in everyday life allows technology to reproduce some of the user’s tasks at an automatic level. Ability is determined by a program that is pre-programmed with a set of machine learning or deep learning algorithms. AI works 24 hours a day, seven days a week; it does not need rest. It allows devices to perform various functions, make rational decisions, and avoid critical errors. What is IoT? The Internet of Things (IoT) is the ability of devices to transmit data to each other over the Internet. Both household appliances and industrial installations can have this property. In addition, the technology allows devices to assess the situation and draw conclusions without human consent. Integration of assistants When technologies are introduced into the “Smart Home” system, all the necessary information from the Internet of Things goes to the artificial intelligence base, which already carries out a prepared algorithm of actions. AI transforms the received data into commands, which, subsequently, are formed into a model of behavior that fully meets human needs. This is due to the ability of technology to analyze the results obtained after contact with a person and predict further options for the development of events. Assistant integration is ubiquitous, and even giants like Apple, Google, and Amazon adopt them for automation. With their help, users can issue commands to their devices from a distance and ensure that everything will be done without errors. Similar actions are carried out from applications. It should be convenient and usable and not contain grammatical errors. If you want to develop one of these solutions, you must approach the question as cleverly as possible. Every detail is essential, from the interface to typos. By the way, tools like Fresh Essays, Grammarly, etc., will help to avoid this.

In agriculture, like in other industries, the Internet of Things promises formerly unattainable efficiency, resource and expense savings, automation, and data-driven operations. However, the combination of IoT and Agriculture is really very beneficial. These advantages aren’t enhancements; they’re remedies for a whole industry grappling with a slew of serious issues. Exceptional efficiency Agriculture is now in a contest. Farmers must produce more with deteriorating soil, decreasing land supply, and growing weather variability. Farmers can monitor their products and conditions in real-time thanks to IoT-enabled agriculture. As a result, they have quick insights, can identify problems before they occur, and make well-informed judgments on how to prevent them. IoT solutions in agriculture also include automation, such as demand-based irrigation, fertilization, and robot harvesting. Growth 70% of the world’s population will live in cities by reaching 9 billion people. IoT-based greenhouses have enabled Short food supply chains and hydroponic systems, which should be able to feed these individuals with fresh fruits and vegetables. We should grow food in supermarkets, on the walls and rooftops of buildings, in shipping crates, and of course, in the comfort of everyone’s home, thanks to smart closed-cycle agricultural systems. Resources are scarce Plenty of agriculture IoT solutions are focused on maximizing the use of resources—water, electricity, land. However, highly precise farming with IoT relies on the data obtained from varied sensors in the field, which allows farmers to correctly distribute just enough nutrients within one plant.

The world’s most successful companies set their focus on customer satisfaction. The reason being that customers leave organizations where they are not satisfied with the service. New products with unique and improved features will continue to pop up in the market. Still, the customer would rather continue doing business with companies that serviced them well over time. This is why companies have to pay apt attention to customer loyalty and advocacy. Data Science in Improving Customer Satisfaction The advent of new technologies and the utilization of data science methods on huge amounts of data makes it easier for companies to place laser focus on the factors that cement customer loyalty for their products. Companies across the world now invest time and money in data science, analytics, and statistical testing. Data scientists help businesses navigate their way through the vast ocean of data available to them in a bid to make the right, timely business decisions. How B2C & B2B Companies Use Data Differently Data analytics is a source of valuable insights that can inform how both B2c and B2B companies make decisions about products, marketing, and sales. Though they each have a unique set of challenges, B2c and B2B businesses both collect, visualize, and analyze their most valuable asset – customer data. Both B2B and B2C companies use data analytics to unlock new pathways to increase customers, more profits, and better decision-making. But they access these pathways in totally different ways. So let’s go over the differences between how B2B and B2C companies use data. Sales Data B2C businesses often have shorter sales cycles, with a large part of their revenue coming from advertisements. This implies that the customers need to be engaged for longer and the sales cycle optimized. Leveraging data on the customer’s experience in making a purchase can help point decision-makers in the right direction. B2B companies, on the other hand, have much longer sales cycles. Here, the goal is to minimize the amount of time the customer spends making a purchase. Using data science, the company can improve efficiency and shorten the sales cycle. Data scientists can analyze sales data for insight into improvements in customer experience. Customer Data Since B2C companies typically have more customers than their B2B counterparts, there is usually no shortage of data to analyze. This allows data scientists to analyze several different customer data points related to their experience with the business. Data scientists can use customer data to segment customers accurately and outline better user personas to guide product and marketing initiatives.

There has been a gradual but wide-scale shift in the business world, compounded by the movement restrictions and other impacts of the COVID-19 pandemic, to a remote work model. These changes have led to the need for effective next-gen network security for businesses. As the nature of work changes, there must be a corresponding reevaluation and subsequent transformation of how organizations approach network security. Ultimate Guide to Effective Next-Gen Network Security for Organizations Moving work to the cloud via work-from-home policies eliminates the physical boundaries of cybersecurity. Moreover, this extension of the traditional bounds of network security establishes a strong basis for the greater adoption of edge security practices. Apparently, end-to-end security now seems more like edge-to-cloud security. This transformation is not just about technologies and tools, although those are critical in adapting networks and cloud environments to the new model. Rather, this transformation is, foremost, a change of outlook. Data and Network Security With the increase in the number of technological tools at work, including and especially IoT devices, more data is being collected. And the more data is collected, the more effort must be exerted in protecting the information from intruders. This supports the earlier submission that the new normal in network security is not just around transformation but more an extension. An extension of security capabilities to accommodate the revolution of attack approaches. Basically, when it comes to network security, like all other organizational processes, business leaders must think in scale. After all, cyber attackers are not backing down; instead, they devise newer and newer means of network intrusion and system destabilization. Change and Adaptation It is understandable why some leaders may first prefer to dip their toes into the water; the world has not witnessed this scale of a comprehensive upset in a long time. Yet, the greater mistake, and one that supports that form of approach, unfortunately, is that many people believe that the time and the current scale of challenges we now face would eventually pass.

Artificial intelligence is gaining more and more attention. Intelligent self-learning programs disrupt many industries, including eCommerce, manufacturing and production lines, transportation, agriculture, logistics and supply chain, and more. Moreover, such programs automate redundant processes and don’t require a high level of creativity, increasing its overall effectiveness. “It is difficult to think of an industry that AI will not transform. This includes healthcare, education, transportation, retail, communications, and agriculture. There are surprisingly clear paths for AI to make a big difference in all of these industries.” –  Andrew Ng, Founder, and CEO of Landing AI Innovative Application of AI in Recruitment These disruptive forces have started hitting the HR industry as well. And it’s not just a trend; the innovations brought by AI are going to stay. Moreover, it’s anything but a temporary phenomenon. The most recent development in HR technology is AI in recruitment. The changes brought by AI in recruitment will be significant since many recruitment aspects have redundant, time-consuming tasks that can be easily automated. Apart from that, AI can bring innovative solutions to the new-age emerging problems faced in HR and recruitment, like managing a multi-generational workforce, rising mental health issues, promotion, or inclusive culture. The entire HR industry will be going under major changes while AI makes their jobs easier, faster, and better. This article will explore the role of AI in recruitment, its possible use cases, top tools available in the market to automate recruitment processes, potential challenges attached with the adoption of AI, and its overall impact. The Role of AI in Recruitment — nine helps for recruitment Intelligent Screening According to 52% of talent acquisition leaders, the most challenging part of recruitment is screening and short-listing candidates from a large talent pool. When integrated with applicant tracking software (ATS), an AI screening software can make hiring recommendations by utilizing data like candidates’ performance, merits, experience, etc. The AI screening software can learn from existing candidates’ experience and skillsets and make recommendations accordingly.

Manual operations in manufacturing often lead to increased costs and decreased growth. Manufacturers have to resolve 4 critical challenges: operations optimization, cost savings, production quality improvement, and demand forecasting. Digitizing one or two processes can only work to an extent and only a complete digital solution could come in handy. Especially, critical challenges like demand forecasting require a robust prediction system based on operation data analysis and without this manufacturers can never plan for the future. Predictive Analytics in Manufacturing – Why it Matters and How it Works So, what would be the best possible way to address these challenges? An interesting yet best way to overcome this challenge is by automating the process with predictive maintenance solutions. Let’s get started with the applications of predictive maintenance in manufacturing across improving operations and production quality at reduced cost and forecasting demand for the future in detail in the sections below. What is predictive maintenance? “Predictive maintenance (PdM) is maintenance that monitors the performance and condition of equipment during normal operation to reduce the likelihood of failures. Also known as condition-based maintenance, predictive maintenance has been utilized in the industrial world since the 1990s. The goal of predictive maintenance is the ability to first predict when equipment failure could occur (based on certain factors), followed by preventing the failure through regularly scheduled and corrective maintenance.” (Source: Reliable Plant) Manufacturing Predictive Analytics Market Outlook 2018 to 2026 “The manufacturing predictive analytics market size was valued at $535.0 million in 2018 and is projected to reach $2.5 billion by 2026, growing at a CAGR of 21.7% from 2019 to 2026. The advent of Industry 4.0 boosts substantive recent innovations in manufacturing.” (Source: Allied Market Research) How the entire predictive maintenance system works A predictive maintenance system comprises the Internet of Things (to collect data from any surface); Cloud (to process the data); Mobile applications (to push notifications based on data); AI/ML (to analyze and predict insights using data); web application (to share entire operations data under one roof).

The realization of the necessity of an interconnected system that leverages the Internet to make things easier revolutionizes the way we live. It led to the creation of IoT, and although the term is 16 years old – the concept dates back to the 70s. Previously known as “Embedded Internet,” the term IoT was coined in 1999 by Kevin Ashton. A Comprehensive Overview of IoT, Big Data, Cloud Computing Today, IoT is the primary source of big data collection. The analysis and processing of this gathered data have given numerous modern analytic solutions. IoT is also the main reason for innovation in the modern world, with more robust information. It has given rise to new business opportunities. Today, IoT technology has given a new meaning to the world “Smart.” By forming a relationship with other technologies like cloud computing and contributing to them in terms of information, the IoT technology helps new businesses and old ones in terms of growth. Cloud computing advances processes and data analytics For example, cloud computing has been advancing processes and data analytics in an economical and scalable manner. Such empowering capabilities are being provided to brands by the generation of Big Data through IoT. Moreover, IoT is also responsible for generating analytics solutions that, without Cloud, were costly and complicated due to a complex infrastructure or architecture and storage and processing requirements. Since the IoT was a data-driven technology, it contributed significantly to Big Data, influencing various velocity, accuracy, and reliability domains. In a nutshell, the IoT is the future of businesses and lifestyles. With the integration of Big Data and Cloud, more innovative digital solutions that consist of better, more advanced analytics and data-oriented decision-making characteristics are becoming increasingly possible. Since IoT is a vast and continuously evolving field, it is getting difficult to understand the technology and its benefits. So, in this article, we’re going to explore a comprehensive overview of What is IoT? We will explain the relationship holistically between IoT and Big Data and IoT and Cloud. We will also cover some of the advantages of using IoT integrated Big Data and Cloud computing.

The digital world has been entirely transformed with the help of technological breakthroughs, and IoT (Internet of Things) is to be credited among AI (Artificial Intelligence), ML (Machine Learning), Data Science, and more. Internet of Things has been the futuristic concept of connecting and controlling our devices and items remotely. This future idea alone has brought drastic change within many industries that have seen improved processes, increased productivity, and many other benefits. IoT for the Disabled – Breaking Barriers and Changing Lives However, one of the most significant contributions that IoT has made in assisting users with disabilities. How IoT for the disabled? We’ll get to that thought in this article. For now, let’s shed light on the concept of IoT for our readers that would like to understand the technology first. What is IoT? The Internet of Things can be explained as a network of physical objects with sensors, software, and various other technologies embedded within them to connect and exchange data with other devices, systems, or mobile apps over the internet. What could be those devices? They could range from regular household items, medical equipment, or industrial tools. Today, we have nearly 7 billion connected devices, with experts expecting the numbers to spike up to 10billion by 2020 and 22billion by 2025. How Is IoT Important? IoT is the upcoming technology of the 21st century that has allowed human connection with everyday objects like kitchen appliances, cars, house lights, and much more, enabling data sharing without any human intervention. Basically, an ordinary item can transmit data and automate tasks without any manual control, giving new waves of opportunities to contactless during the COVID times and otherwise. Not to mention, with low-cost computing, big data analytics, and mobile technologies, the Internet of Things is relatively cheap and easily accessible to the masses. Of course, IoT comes with its own challenges and trends that should be kept a close eye on, not to mention the many security challenges that IoT faces. Speaking about trends of IoT, ‘AIoT’ is also a reality that includes AI playing a big role in changing three industries in particular.

How often do you use a smart device at your home? Indeed several times, knowingly or unknowingly. Be it a smartphone, wearable, personal electronics, smart bulbs, or tablets, these devices have become an integral part of our lives. Our homes now have multiple smart devices that are considered “intelligent devices.” However,  the trend for smart spaces or cities extends far beyond our homes. We live in a time of urban transition. Increasingly people are flocking to cities, and cities are evolving rapidly. The UN predicts that 68% of the world’s population will live in urban areas by 2050. Accommodating more people is not only a challenge but these cities are trying to work with “quality of life and sustainability,” which are the key issues everywhere. Smart city initiatives can address these issues. What smart city looks like? A smart city concept focuses on utilizing technology to effectively manage the city’s assets and resources to improve the quality of services, and hopefully, life for its residents. The technology comprises six building blocks. It encompasses what is termed, smart people,  smart city economy, smart mobility,  smart environment. It also includes — smart living and smart governance — that together can contribute to the realization of smart city strategy by augmenting social inclusion, technological inclusion, economic development, and environmental sustainability to drive the smart economy. Smart People Smart people being at the heart and the fundamental block of the smart city system requires attributes like professional excellence, high Human Development Index, integrated education system, attracts knowledge workers, inhabitants opts for e-learning models, embraces technological changes, maintain a healthy lifestyle, and contributes towards making the city more liveable. Smart city residents have to be more involved. But how is that possible? Thanks to technology.   Let’s look at the example, wherein citizens can utilize apps that allow them to report local issues more easily or community networking platforms that allow neighbors to connect and share resources. This is just one, there are several ways in which technology can help. Therefore, developing a center for learning new technologies, and encouraging investments in technology are essential.

It seems like yesterday that Millennials were the new renters on the block, slowly taking over from Gen Xers to become the new majority. Suddenly, Gen Z is beginning to gain ground on Millennials, entering the workforce en masse and looking for somewhere to live other than their parents’ homes. By 2034, Gen Z — Americans born between 1997 and 2012 — will overtake Millennials as the largest portion of the U.S. population. Today, about 44 million Gen Zers are looking to rent (updaterdotcomblog) — 60% of the entire generation. This represents the most intense demand for rentals in decades. At first glance, it might not seem like much has to change to accommodate this influx of new renters. Millennials and Gen Zers often feel like two sides of the same coin: Both groups tend to be tech-savvy, and they both faced a recession upon graduating from college. However, there are noteworthy differences between the two generations regarding technological preferences in their homes. Gen Zers grew up along with the Internet of Things (IoT), and they connect with technology more than any other generation. Gen Zers Aren’t Just Younger Millennials While most Millennials know their way around a smartphone, being tech-literate and tech native are two completely different things. Gen Zers are tech natives who grew up with smart home devices, smartphones, voice assistants, social media, etc. They are the “all digital natives. ” In one survey, 60% of Gen Zers said they had used smartphones before they turned 14. They’ve been in the middle of it all, adopting the newest technology even as it evolved at a more rapid pace. Unlike Millennials, technology isn’t just a part of the Gen Z lifestyle — it is their lifestyle. In practical terms, this means that Gen Zers expect more from their technology than previous generations. Technology feeds their connected lifestyle — which, in turn, informs every decision, including where they live. Much like electricity or water, high-speed internet access and a smart home that can be controlled remotely will be considered necessities rather than conveniences. Though many Gen Z members have not yet bought homes, 43% say that smart home capabilities, like connected IoT devices, are a key consideration in choosing where they live.