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How Blockchain and AI have improved the World?

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How Blockchain and AI have improved the World?

In one way or another, both blockchain and artificial intelligence have laid the groundwork for a new commercial era. Have you ever considered what would transpire when these two technologies converge, though? Keep reading to know further. 

Real Perks of Powering Artificial Intelligence with Blockchain 

The fundamental objectives of blockchain are to update, safeguard, and guarantee the authenticity of all records. However, AI is required for decision-making, evaluation, and the simplification of independent interaction. Future development of more reliable intelligent systems will be made possible by the seamless integration of these two technologies. Here are the main advantages that businesses will gain from the combination of blockchain and AI.

  • Security- Business organizations are looking for a potential solution to strengthen the security of the online data amid fears of cybersecurity breaches. Information theft and hacking are on the rise. Blockchain technology can help these businesses, especially banks and insurance providers. Their data can be kept secure by creating the blockchain network’s transactional procedures. These businesses only need to utilize their current security protocols. When designed to act autonomously, machines need a higher level of security. The problems with internet security can be solved by blockchain.
  • Decentralized Control and Data Sharing- A decentralized network of nodes powers the blockchain. When these networks cooperate, they can solve difficult algorithms. AI functions on a similar mechanism. The AI-based systems consider all the potential solutions before making a decision. Before selecting the optimal option, the system assesses all the options. Blockchain, on the other hand, splits the task across all the nodes rather than completely solving it. These are widespread around the world and number hundreds. Thus, the procedure significantly accelerates. For secure and intelligent systems, experienced mobile app development companies are cooperating with business enterprises prepared to create strong AI-based solutions on blockchain.
  • Open Data Market- As AI develops, it depends more and more on the data that is accessible, which comes from various sources. Although major corporations like Amazon, Google, & Facebook have access to vast data sources that can be useful for creating AI applications, these resources are not readily available on the open market. By incorporating peer-to-peer connectivity, the blockchain technology and AI will work together to quickly solve this problem. As a distributed & open registry, the data is readily accessible to all network members. Thus, the data oligopoly that is currently visible in cyberspace will vanish.
  • Handling Data on Higher Scale- Scaling data is the most difficult challenge once it is available. An estimated 1.3 zettabytes of the data flow across cyberspace each year. One specific branch of artificial intelligence, known as artificial general intelligence, can be used to provide feedback in a control system. Autonomous agents in fact will be capable to communicate with the physical environment more effectively as a result. At the moment, blockchains are being used to store a ton of data. Business organizations gain a variety of advantages from this over the conventional decentralized storage system. The data won’t stay in one place in the event of a crisis or a natural disaster affecting the company. Large volumes of data are protected in the decentralized system because of this. These are less susceptible to corruption since they are resilient to hacks.
  • Control Data Use and Models- When blockchain and AI are combined, it’s crucial to think about how to control data consumption and models. For instance, if someone wants to submit anything to Facebook or Twitter, they must first seek the necessary permissions when logging into their accounts. For AI data & models, a same idea applies. Due to the authorization required during the procedure, you can encounter some limitations when creating data for the model. AI will be able to use blockchain technology, which will streamline the process.

Effect of the Convergence of AI-Blockchain on Various Industries 

In practically every industry, blockchain technology and artificial intelligence are being used in similar ways. To make the process easier, let’s examine the effects of blockchain and AI collaboration on each industry separately.


Blockchain and artificial intelligence in the healthcare sector are both creating new prospects for patients and independent healthcare service providers. But after everything is said and done, patients and healthcare organizations will receive services at a new level. The intersection of blockchain and AI in healthcare will provide the chance to protect medical records from cyberattacks, access the data in a decentralized layer, and give people ownership of their data. It will also eliminate the monopolistic power of the top tech giants like Google and Apple, and it will enable patients to share the data with anybody on their terms and receive tailored responses.


The influence of AI on the retail industry will be increased by combining it with blockchain technologies. If their marketing strategy is unsuccessful, it will enable retailers to record the entire process and save customer insights in immutable blocks so they can identify the contributing elements. Additionally, it will improve payment procedures and eliminate fraud risk.

Supply Chain 

Combining blockchain with AI benefits will create a brand-new universe. The technologies will work together to optimize the supply chain in a way that is more secure and efficient and will also provide better understandings into what should be eliminated in the first place. As a result, everyone’s experience will be improved, and business earnings will increase.


AI and blockchain integration will also speed up financial sector procedures. AI will reduce reliance on humans to know human emotions and forecast the next course of action, which will ultimately improve automation and performance level, whereas Blockchain will instill industry trust through Smart Contracts.


To redefine democracy, blockchain and AI are merging their respective fields of expertise. By using technology, it will be possible to retain data security and quality while transferring control over the data from a large group of people to the general public. Additionally, e-voting processes will be tracked by AI and Blockchain technologies, making them instantly available to all citizens.

Mobile Applications 

In essence, combining blockchain with AI can speed up response times and boost efficiency. For instance, a payment needs to be made. Blockchain will therefore improve speed by making the payment route streamlined and transparent. AI will simultaneously determine which payment gateway should be used and how the client plans to complete the transaction. By accelerating the payment page in this manner, both technologies will improve the checkout process.

Bottom Line 

The idea of fusing blockchain technology and artificial intelligence is still in its infancy. While the integration of such technologies via AI development companies and blockchain development companies has seen some success, it is still in its early stages. As a result, we must still wait before we fully grasp the opportunities this integration presents and how to seize them.



4 Key Factors Propelling Airport Security Surveillance Demand

To ensure that the level of security is at an all-time high, airport security experts have been taking drastic measures, including cabin checks and the deployment of armed or unarmed security guards.

Even during the COVID-19 pandemic and consequent staff shortage at airports, government bodies continue to conduct a range of procedures to enhance security screening procedures.

In 2021, the Transportation Security Administration introduced new protocols to facilitate a smooth and safe screening process to address the burgeoning passenger traffic, such as the adoption of CT
(computed tomography) units to provide 3-D images of carry-on bags’ contents. As per the Federal Aviation Administration, there were more than 5,550 reports of unruly passengers between January and December 2021, which could drive airport security market demand over the years ahead.

With the growing number of air passengers, several aviation agencies and government bodies are focusing on embracing new technologies and improving surveillance and access control across multiple airports.

Following are 4 prominent factors bolstering airport security industry expansion:

  • Deployment of IoT and AI tech in analytics and security systems

Airport stakeholders are consistently developing visions for the digitalization of airport operations and digital terminals through automation and innovative technologies. New information and

communications technologies like AI and IoT sensors are at the peak of inflated expectations to induce these changes, contributing to the revolution of airport security systems.
To deliver a high level of security, GMR Hyderabad International Airport Ltd. announced the implementation of Queue Management Systems in June 2021. These systems combined AI video analytics and IoT security cameras to reduce waiting time at passenger touchpoints, thus enhancing passenger experience and safety.

  • Technological innovation in aviation sector

While AI technology is increasingly used to automate security checkpoints in the aviation industry, adversarial AI can cause ML models to wrongly interpret inputs and behave in a manner favorable to attackers. As a result, cyber-security risks may evolve rapidly, and the low costs of cyber-attacks can make them easily affordable to criminal and terrorist organizations, creating a major hindrance to procedures like automated airport security checking. As per the European Aviation Safety Agency’s estimates, over 1,000 attacks occur on aviation systems per month, emerging as a threat to airport security, safety, and reputation. Despite the rising number of attackers and the risks of technological advancement, however, AI also comes along with a range of opportunities capable of increasing the efficiency of airports, thereby augmenting the demand for airport body scanners and other security equipment.

  •  Regulatory frameworks and workshops against terrorist attacks

Numerous legal frameworks and regulations have been introduced worldwide to prevent and effectively respond to terrorist acts against maritime and air transportation. Out of the 19 international legal instruments, 12 of them are related to terrorism prevention in the international civil aviation and maritime navigation sectors.

Also, in an attempt to address terrorist attacks in airports, the APEC (Asia-Pacific Economic Cooperation) CTWG (Counter-Terrorism Working Group) held a virtual workshop on the Soft Target Protection in an Aviation Ecosystem. This workshop was aimed at discussing the challenges associated with soft target protection across the commercial aviation sector. These initiatives could encourage the usage of airport security scanners and other cutting-edge devices to help airport systems respond and recover from
terrorist attacks.

  • Spending on airport upgradation projects

Following a decline in capital expenditure during the initial months of the COVID-19 pandemic, the U.S. Department of Transportation’s FAA (Federal Aviation Administration) granted around $845 million for projects at over 388 airports in 49 states as well as the District of Columbia in July 2021. Tucson International Airport was among the recipients of this grant and obtained $22.4 million for the overhaul of the Runway 11R/29L and the airport’s safety enhancement program.

In addition, a partial recovery in capital investment by over 14% to $12 billion was expected in 2021. With the gradual revival of airport business from the pandemic disruptions, the airport security market
is projected to grow substantially over the coming years.


Taking The Mystery Out Of AI: 4 Ways It Makes Life Easier

Artificial intelligence is significantly impacting the world, yet there’s still a great amount of mystery – and misconceptions – about it.

The public’s imagination has been heavily shaped by science fiction, with the term AI evoking images of robots like WALL-E, C3PO from Star Wars, and David from Stephen Spielberg’s movie A.I. Scientists and technologists refer to this kind of humanlike AI as “general artificial intelligence.” General AI attempts to mimic the kind of abstract thought and typical problem-solving skills seen in humans.

I say attempts because there is currently no existing general AI system even approaching the sophistication of the human brain. The technology is nowhere close to creating a system capable of abstract thought or general intelligence. But “applied AI” is rapidly becoming a mainstream technology, improving the efficiency and profitability of businesses in many industries.

Why applied AI is faster but not yet smarter than us 

Current AI systems, for all their computational ability, do not have the ability to understand and analyze context the way human brains do. For example, we can see a barking dog and instantly determine the threat level. Sufficiently advanced AI can recognize the dog but may be unable to determine the breed, its physical agility, and whether it has been encountered before. Unlike humans, AI cannot connect dots and judge context to solve problems creatively.

But AI systems can make decisions far more rapidly and accurately than humans. The strengths and limitations of the current generation of artificial intelligence make it most applicable for solving fit-for-purpose business problems. (Fit-for-purpose is the concept in which a product or service is adequate for the purpose for which the consumer selected it.) AI systems are designed to handle a specific task while operating within imposed contextual constraints. These fit-for-purpose systems and tools are known as applied AI.

There are four primary business applications of applied AI in industry. Here is a look at each and how they create efficiencies and value:


Automation saves countless man hours and resources, as computers can process

data in a fraction of the time it takes humans. Some of these processes require decision-making. This is where AI comes into play. Most business processes involve a structured set of inputs, and decisions are made based on defined policies and guidelines. The variables in the equations are well known and operate within a narrow context. Algorithms can make these decisions rapidly and accurately.

These algorithms allow much of the workload that companies do to be offloaded onto automated systems. That advancement provides conveniences for consumers in the age of online shopping. Capital One Shopping, for example, offers customers a browser add-on claiming to save money by automatically comparing prices, applying promo codes and providing deal alerts.

Banks use AI to automate the loan process. Relevant financial records are collected automatically, validated, and analyzed. The system can give a recommendation on the loan before a lender ever sees the application. This may sound frightening and impersonal, but these systems actually assess loans more accurately and fairly than humans. They look at a borrower’s credit history, credibility, liabilities, and other factors and make an impartial decision. Quite often, these individual metrics are also calculated by AI. Credit scores, for example, are calculated automatically.


The data produced by automated business processes holds valuable insights. These insights can be about almost anything; they may reveal something about a business process, unlock untapped opportunities, or even allow companies to make predictions about the future.

The data analysis that leads to insights is mostly automated. Given the volume of data that companies now work with, we need these automated AI systems to find the signal in the noise. AI looks for patterns and makes decisions based on training and defined guidelines. The exponential power of these systems can be seen in machine learning.  IBM Watson, for example, can predict when an elevator is going to fail. AI systems are able to return insights about insights into their own operation, and this allows them to improve their data sets and algorithms. As a result, AI systems draw insights that the designers may not have ever considered or been looking for.


Insights have many applications, but one that is rapidly transforming industries is personalization of user engagement. The insights drawn from consumers, users, and other stakeholders can be used to improve their experiences by engaging with them in a personalized manner.

There are many ways companies can use data to personalize the experience for the stakeholders they serve. Google maps knows through habits a driver’s route and daily schedule and will give them an outlook for the day based on the current data. Retail companies have their websites feature inventory designed to appeal to the specific viewer. Online ads are micro-targeted at individuals based on insights into their specific consumer behavior. Social media platforms also customize news feeds to increase user engagement. Search engines provide results that are tailored to the user’s location, demographics, search habits, online shopping history, and other data.


Sensing produces a kind of insight that deserves special mention due to its revolutionary potential. The exponential explosion in data and computing power now allows us to better recognize patterns as they are forming and predict how they will develop, which in turn allows us to actually sense trends as they form and develop.

This ability has huge business applications. Consider the sudden rise and success of TikTok. ByteDance, the Beijing-based parent company that developed the app, hit it big by filling an emerging niche for teens who could use a platform for recording and sharing short videos. TikTok noticed the trend among teens, built a dedicated app, and marketed it to the emerging user base as the trend developed. TikTok is now worth billions of dollars and is changing the social media landscape.

Many companies using applied AI have built fortunes and improved the world for billions of people. They did so by leveraging exponential technology and riding the development curve. We can likely achieve higher levels of AI-powered efficiency and improvement in all industries.


Rajeev Ronanki ( is the president of digital platforms at Anthem Inc., and the ForbesBooks author of You and AI: A Citizen’s Guide to AI, Blockchain, and Puzzling Together the Future of Healthcare. Before joining Anthem, Ronanki was a partner at Deloitte Consulting, where he spearheaded a myriad of technological healthcare innovations. Ronanki is a frequent contributor to Forbes and other publications. He earned a bachelor’s degree in mechanical engineering from Osmania University and a master’s in computer science from the University of Pennsylvania. 


4 Major Trends Propelling the Growth of Automated Infrastructure Management Solutions Market by 2027

There has been a significant rise in the number of data centers globally over the past few years, driven by the increasing storage and computation requirements to serve applications based on machine learning and AI. This has strongly influenced the adoption of automated infrastructure management solutions and systems across data centers worldwide. The demand for these systems is being further stimulated by the rising penetration of connected consumer electronic devices which is opening new growth opportunities for the automated infrastructure management solutions market.

The market growth is also being accelerated by the growing proclivity towards renewable power generation. AIM solutions help in enhancing the grid efficiency, reliability, safety, and resilience for energy and utilities. They also aid in increasing decarbonization through cleaner electrification and real-time climate data management.

As per the recent report by Global Market Insights, Inc., the automated infrastructure management solutions market is projected to surpass USD 4 billion by 2027, considering the following trends:

New product launches by major companies

Various major companies active in AIM solutions industry are focusing on the development of innovative infrastructure management tools to effectively meet consumer demands and consolidate their position in the market. Quoting an instance, in 2021, RiT Tech, a leading provider of converged IT infrastructure management and connectivity solutions, launched automated infrastructure management tools, designed to bring real-time visibility, control, and monitoring of the entire network physical-layer components.

Burgeoning demand for device discovery solutions

Device discovery solutions find extensive application in various industries owing to their ability to manage the connected environments in real-time. These solutions help in the automatic correlation of performance in all infrastructure tiers for isolating the root cause of problems by detecting the exact device of concern. In addition, they also deliver information regarding the connected devices and their activities in IT infrastructure. Besides, they also help in storing and collecting information about cabling connectivity as well as its connection with other sources through Application Program Interfaces which is fueling the adoption of device discovery solutions further.

Heightened adoption in IT and telecom sector

Growing investments in 5G infrastructure with the shifting consumer preferences for next-generation technologies and smartphones is one of the major reasons driving the adoption of AIM solutions in IT and telecom sector. These solutions provide real-time insight into illegal IT activities along with the automatic recording of all modifications. This in turn helps in improving the asset utilization, reducing the troubleshooting time, offering faster service turn-up, and better network security. In addition, it offers a GIS service that facilitates visualization of locations, engineering architecture, and connections in the physical infrastructure levels as well as the service trail layers and the logical networks.

Expansion of data centers in North America

The continuous growth in the data center infrastructure in North America is largely contributing to the expansion of the regional AIM solutions industry. This can be ascribed to the factors such as increased usage of cloud computing, rise in IoT, and expansion of mobile broadband in the region. In addition, the shifting of numerous data centers and various companies from hardware to software-based services in the U.S. is driving the data center installations. Besides, the increasing penetration of automated connected devices is further impelling the adoption of data center management solutions, complementing the business expansion.

Briefly, the automated infrastructure management solutions industry is growing with the adoption of advanced technologies like AI, IoT, and machine learning, coupled with the expansion of data center infrastructure globally.

Source: Global Market Insights Inc.


automation tompkins

Automation Versus Human Innovation: How To Engineer An Equitable Economy

Are some companies moving closer to having more robots than employees?

Recent studies indicate a trend in that direction.

The data: Research from Google Cloud shows two-thirds of manufacturers who use artificial intelligence in their day-to-day operations say that their reliance on AI is increasing. And a report from PwC predicts that by the mid-2030s, up to 30% of jobs could be automated.

The key questions: How much automation vs. how much human innovation? Which is better for a sustainable economy? And why are some businesses spending more on automation than people?

Thought leader’s take: Jarl Jensen (, ForbesBook author of The Big Solution: Deactivating The Ticking Time Bomb Of Today’s Economy, says large inequities between the labor class and corporations exist in part because of cheap lending practices, enabling corporations to borrow large sums from banks – and one result is the trend toward more automation.

“Corporations would rather have an employee base full of robots, and a select few humans to monitor the robots, because it saves them money in labor cost,” Jensen says.

“Borrowing without a maximum limitation means it is easy, and often more affordable, for corporations to invest in automation or robotics than their labor force. It is cheaper to take a loan from a bank to finance the purchase of artificial intelligence software than it is to re-train workers or engage in improving work skills. The unfortunate reality of our economic system is that there is no incentive for banks to stop making loans to rich people and corporations – even if the end result is a decrease in jobs due to automation and artificial intelligence.”

Jensen thinks the economy can be engineered to make it more equitable – ”an economy for the people.” These are three of the tools he suggests to fix the economy:

Direct deposits. “The first and best tool at our disposal is the money that a new and better version of the Federal Reserve would deposit directly into the bank accounts of every American of working age,” Jensen says. “This is not a basic income. It is an essential liberty.”

Jensen’s idea is that the direct deposits would be made for future work. The amount each working person would receive would be adjusted according to the signals being received from the economy.  “The way out of the debt trap is direct deposits,” he says. “Direct deposits put the people first. It forces the system to adjust to the needs of the people. The money we’re talking about for these direct deposits is money that the Fed simply creates out of thin air like it does when it issues money for loans to banks. But this money is not creating a debt that has to be repaid, thus does not grow the national deficit or become a debt burden for the Americans who receive it.”

Blue sky markets. Jensen describes blue sky markets as money for businesses that pursue the common good. This tool, he says, takes big problems out of the government’s hands and puts them in the hands of entrepreneurs. ”Blue sky markets issue money directly to fund commodity exchanges that effectively solve these big problems,” he says. “They create money for the purpose of fixing what is broken and making a more sustainable, stable, and compelling future.”

One example of implementing this tool is in addressing climate change. “Businesses would bid on the exchange to remove CO2 from the atmosphere,” Jensen says. “Money that is not debt-based, taken directly from the Federal Reserve, would pay the lowest bidder to remove the CO2. Competition for profits would compel entrepreneurs to figure out how to do it efficiently and effectively.”

New kind of savings account. “Today, any money you put in the bank doesn’t sit in your account,” Jensen says. “It gets repurposed. The bank uses it to invest, to loan out to other people or entities, and to create more debt. But if, alongside these new direct deposits, you had new high-interest bank accounts that are accessible to everyone, then that would keep some of the money out of circulation. Many people would choose to save the money and collect the interest.”

Jensen says the money to pay those higher interest rates would come from the Fed. With more people saving because of this high-interest incentive, and much less of that money going out in circulation, he reasons that inflation would not set in despite all the direct deposits and blue sky markets. “And as a huge bonus,” he says, “this system makes planning for retirement a lot easier.”

“Having an economy for the people is all about reimagining how we value money and restructuring how banks do business,” Jensen says. “It’s about real freedom, sustainability, and the optimization of society.”


Jarl Jensen ( is ForbesBook author of The Big Solution: Deactivating The Ticking Time Bomb Of Today’s Economy. He’s the founder and president of Inventagon, a company creating simpler research and development solutions for organizations across the globe. Jensen holds patents for medical technologies that have reached sales of over $1 billion. He founded EuroMed, a company he sold in 2016, and has written five books about the economy and its relationship with society.


Smart Cities of the Future Rely on Innovation, Critical Discussions

In the Chinese city of Hangzhou, an AI-based smart technology called “City Brain” has helped reduce traffic jams by 15%. During the pandemic, New York City analyzed data related to spending pattern changes in specific neighborhoods to better allocate aid disbursement and investment priorities. And San Diego was lauded for approaching city-building with a “citizen-centric focus”, thanks in part to its use of mobile apps, and expansion of open data, along with its Get It Done citizen reporting tool.


Smart cities are sprouting up around the globe at an increasing rate, and they are quickly becoming model frameworks for future-ready urban centers seeking to level up how they collect and parse citizen data. What they all have in common is how they invest resources and time into developing city-centric solutions to address the wide swath of city challenges: waste and water management, public safety, transportation, air quality monitoring, traffic and parking, public works, municipal Wi-Fi, and more.

What the future of cities relies on, especially as they all recover from a devastating pandemic, is the innovation brimming across hundreds of projects built to answer a critical question: how can we leverage the data from smart city technologies to digitally empower cities to adapt and thrive?

When cities smarten up, everyone wins

For cities considering the pros and cons of adopting new technologies, it’s hard to argue with the data: By 2025, cities that deploy smart-mobility applications have the potential to cut commuting times by 20% on average, with some people enjoying even larger reductions, a McKinsey report found.

Take the sprinkler your neighbors automatically ran this weekend after it rained. If cities deployed sensors and analytics to water consumption patterns, which pairs advanced metering with digital feedback messages, it can urge people toward conservation and reduce consumption by 25% in cities where residential water usage is high. While currently, much of this IoT technology and data is owned by the private sector, it’s critical to bridge this gap in order to help the public better understand their behaviors and impact through data. Additionally, access to this data will enable cities to make better decisions about public resources and amenities.

The more data a city can collect about its citizens’ habits, the more sense they can make of which resources can be allocated where. And it can save lives, too. In Nevada cities, Waycare’s predictive AI delivers an 18% reduction in primary crashes and a 43% reduction in the percentage of speeding drivers along key corridors.

Some cities haven’t caught up to the shining examples of layering data collection and real-time analysis in urban centers. More often than not, they are encumbered by bureaucratic and outdated approaches to data collection.

There’s a disconnect between the municipalities and corporations that may have IoT data and the stakeholders, including those same cities and private developers who could benefit from it, too. Same-old strategies on data gathering, such as physical surveys and endless meetings to pick at each process, should be phased out, and allow for an intermediary to help finesse the conversation between those three pillars of city development.

Also, cities have to address the unease some people may feel about surveillance technology, for example. In China, where that tech has long been the norm, they’re even anxious about how their data will be used by their government: According to a recent survey by tech firm Tencent and Chinese state broadcaster CCTV, nearly 80% of respondents said they worried about the impact of artificial intelligence on their privacy.

Pandemic’s curveball could end up being a home run

If there’s any hand wringing over the state of cities due to the havoc wrought by the pandemic, urban theorist Richard Florida offers some comforting words: “Cities have been the epicenters of infectious disease since the time of Gilgamesh, and they have always bounced back—often stronger than before.”

Some insiders believe that as much as the pandemic crippled supply chains and shut down business sectors across communities, it brought a few silver linings. Data collection strategies accelerated immensely, whether from health care departments or government agencies. The continuing trend of leveraging Internet of Things devices, which connect to each other quickly and remotely, also gave rise to intriguing pairings.

At the state and infrastructure levels, AI and machine learning will likely be matched with IoT for even closer social monitoring as pandemic warning and control systems are established, notes a report from research firm MSCI.

As broadband use skyrocketed during a year of work-from-home policies, rollouts of 5G networks continued at a brisk space, and even picked up in areas that needed high-quality connectivity as soon as possible. Building that underlying network is fundamental to enable seamless adoption of technologies at the heart of smart cities of the future.

Going forward, city planners and developers will work with datasets from businesses who layer various granular data on heat maps via an analytics platform. Understanding the correlation between income levels and access to certain retail, like grocery stores, or access to transit and parks where a neighborhood’s density is rapidly increasing, may be opportunities for cities to identify community needs and work with developers on new projects.

“Six key groups of people should be at the table to discuss where smart cities go from here,” says Chelsea Collier, founder of Digi.City, a consultant specializing in smart city technology.

Those groups should be:

-Government bodies, from local to federal

-Educational institutions, from kindergarten to post-secondary

-Startup entrepreneurs to bring subject matter expertise to the discussion

-Artists and creative who can fuel projects with outside-the-box solutions

-Social sectors such as nonprofits and advocacy groups

-and communities and their citizens

“When everyone listens to each other’s perspective, it’s more useful than just working towards someone’s agenda,” adds Collier.

The smarter the city, the more it’s open to how various sectors, private and public, can drive innovation and growth forward. The future of cities will be written by those players who look beyond their own personal missions and instead cast a wide net to strengthen neighborhoods adapting to a strange post-pandemic era fraught with challenges.


Sara Maffey is the head of industry relations at Local Logic, a location intelligence platform that digitizes the build world for consumers, investors, developers and governments. Local Logic delivers an unrivaled clarity and actionable insights capable of creating more sustainable and equitable cities.

oil and gas

AI in the Oil and Gas Market

Artificial Intelligence (AI) is beneficial to all types of industries. In the oil and gas industry, it stands to make huge gains. The industry is one of the most dangerous because of the constant risk of fires and explosions due to the explosive nature of these fuels. Digital transformation in the oil and gas sector may save about 10% of field operations cost thanks to using augmented visual technologies. AI improves business operations, the productivity of the fuels, and safety. It also lends preciseness to applications such as quality control, prediction planning, and predictive maintenance, all of which affect the running of the business.

AI technologies are used in three ways. The first is in operation, which pertains to the upstream, midstream, and downstream. Upstream deals with the exploration and production sector. Midstream is when the transportation of crude or refined petroleum products takes place. Downstream is the process of refining, processing, and purifying crude oil and natural gas.

The second is service type defined by professional services and managed services. The third is geography, which is segmented into five continent-based areas of the world.

Use of AI In Safety

AI works to optimize operations during the upstream, midstream, and downstream functions. Defects may arise in the pipeline or in the mechanisms used to explore for oil and produce it. Using AI will detect any defects in the machinery or pipeline used to explore, produce, transport, refine and process crude oil and natural gas, enabling the rectification of any identified error. This will save costs and prevent extensive damage that may otherwise have occurred.

AI in the oil and gas industry promotes high safety and security standards. Oil and gas are highly dangerous because of the fuels’ flammability and the production of toxic fumes. AI systems can monitor toxicity levels and leaks and send an alert to rectify the flagged issues.

Another safety hazard in the industry is the change of temperature. Environmental conditions can cause changes in the safety of the storage and transportation of crude oil and natural gas. Early detection is key to make the necessary corrections to avert disaster quickly. AI can automatically adjust heating and cooling systems so that the product remains safe throughout the changing seasons of the year. AI will also help alert the maintenance crew when maintenance is needed on various machinery used to process and transport the crude oil.

AI In Business Optimization

AI aids businesses to predict downtimes, for example, when machinery is being maintained. The business can make arrangements to get alternative equipment, thus preventing loss of income because of better planning.

With proper maintenance, the life of the machinery is lengthened, which results in long-term cost savings.

Data is used in the oil industry to derive information on various plants and assist geoscientists in making strategic decisions. For example, if there is a need to move an exploration plant to another site. AI can quickly process large amounts of data, enabling real-time decision-making that improves overall business operations, leading to efficiency, fewer risks, and damage, which is costly, and cost savings based on improved business processes.

AI-based technologies can also increase the rate of exploration, which is a time-consuming and capital-intensive venture. AI can interpret the geology, geophysics and oil reservoir of a geographical location so that exploration is more precise, thus eliminating the need to spend more money on a hit-and-miss scenario.

AI in Quality Assurance

Artificial Intelligence in the oil and gas industry is great for quality assurance. The industry is highly dynamic, and the risk factors are high. AI-based technologies are designed for seamless applications and limitless uses. This increases the quality of the entire process from the beginning point of exploration to the endpoint of purification and processing crude oil and natural gas. This is done by early detection of any existing or potential risks to be corrected immediately.


The Future of Warehousing

In September of 2018, Forbes Insights published a survey of 400 senior haulage executives. They reported that more than two-thirds of the respondents believed seismic changes had to occur within the logistics sector, otherwise its warehouses would risk not being able to facilitate the growing demand for freight delivery.

Three years and a global pandemic later, and demand for warehouses is higher than ever. So how has the industry endured this tumultuous period? The simple answer is greater investment in technology! Innovators within warehousing have continued to incorporate intuitive software into their models to cut costs, speed up delivery time and improve efficiency.

With this trend of incorporating technologies into the haulage sector only set to continue, the mind boggles at what warehouses could be capable of in the future. To that end let’s unravel the warehouse innovations set to be introduced in the coming years and what the biggest names are doing today to ensure they won’t be left behind.

Warehousing the Amazon way

We would be remiss not to mention Amazon in a discussion about the future of warehousing. After all, their network accounts for over 150 million square feet of warehouse space across the globe.

The company has, since its emergence in the ‘90s, being trailblazers for cutting-edge warehousing models. In the mid-2000s they popularized fulfillment centers whereby sellers could leverage the vast network of warehouses Amazon had to store, pack and ship their customer’s orders for the same standardized fee – no matter where an item was being sent.

Since then, many warehouses have attempted to adopt something similar to the Fulfilment By Amazon (FBA) program and offer to not only store their client’s products but package and deliver them as well. However, none have been able to even rival the FBA. Namely because of one very appealing benefit that FBA offers sellers: Prime eligibility.

This legacy of advancement was further solidified by the recent announcement that Amazon was opening its first robotics fulfillment center in Alberta, Canada. The automated warehouse, slated to open in 2022, is the result of almost a decade-long investment.

In 2012, Amazon purchased robotics company Kiva Systems for $775 million which gave them ownership of a new fleet of mobile robots which were capable of carrying shelves of products from worker to worker and intuitively navigate a warehouse according to barcodes on the floor. Like the FBA program, it’s expected that many warehouses will use Amazon as inspiration and invest in some form of robotics to aid with automation.

Automation for all

As Amazon recognized, automation is the silver bullet when it comes to boosting a warehouse’s operations. Having a workforce that never tires, runs 24/7, and provides a near-perfect output is invaluable. It’s likely that every stage of warehouse infrastructures will have some form of automation in the next few years if they haven’t already.

Drones are expected to have a significant role in the future of warehousing, specifically in aiding inventory control. MIT conducted research in 2017 where they programmed drones to fly above a warehouse floor to read RFID tags from more than ten meters away. The study was a success with the drones only having a 19cm margin of error.

There are currently some safety concerns delaying the immediate integration of drones in warehousing but the continual developments of the technology suggest that we’re not too far away from seeing them introduced.

Automated conveyors and sortation systems have been staples of warehouse infrastructures for decades, now experts are predicting that a third system will become part of every warehouse’s arsenal. The ARC advisory group’s warehouse automation and AS/RS research forecasts that the shuttle systems market is going to grow exponentially.

For context, a warehouse shuttle system is a mobile cart that transports items in pallet racking. It replaces the need for an operative to use a forklift to retrieve stock totes, trays, or cases in a storage buffer. The system, which is also being touted as an essential by various trade groups, provides warehouses with high throughput, scalability, and storage density.

Considering that repetitive tasks can be mechanized fairly easily, there’s plenty of reasons to be excited for what other types of automation could be introduced into warehouse infrastructures and the benefits that they will no doubt yield.

Big Data & AI

Big data and machine learning have revolutionized many industries since their proliferation in the early 2000s and it’s expected to do the same to warehousing.

Order and inventory accuracy, as well as fulfillment time, are all Key Performance Indicators (KPIs) that could be improved through the use of Artificial Intelligence (AI). AI can also evaluate more general drivers that may affect a warehouse’s overall performance including safety, facility damages, and employee productivity. Using this aggregated data AI is able to start automating tasks, collecting the necessary information, and making decisions on its own.

Some industry leaders have already made the transition and began using AI. For example, Alibaba recently fully automated its stocking and shipping warehouses in China by using robots controlled by a sophisticated machine learning algorithm.

Further down the line, many experts believe that more advanced metrics will come into play as well, such as predictive analytics which will give operators a helping hand when it comes to forecasting and drive smarter decision making in the warehouse’s overall operations. Predictive analytics will help with evaluating demand for warehouse space, planning inventory location, responding to supply chain issues, and reducing risks associated with more complex supplier networks.

It’s clear to see that the prospects for warehousing in the near future are bright with plenty of exciting technology currently in use and on the horizon. The industry’s willingness to constantly evolve is truly admirable, with interest in big data, automation, innovative models, and AI at an all-time high. We should all be very excited about the future of warehousing.

Trucking Industry solvento

Artificial Intelligence: The Trucking Industry’s Biggest Asset

About 3.6 million professional truck drivers and another 7.95 million people work in the U.S. trucking industry. It’s an industry well-positioned to benefit from artificial intelligence (AI) technology.

Research firm MarketsandMarkets estimates the AI market within the transportation industry will grow at a compound annual growth rate of almost 18% between 2017 and 2030, and its size increase from $1.2 billion in 2017 to $10.3 billion in 2030.

Truck manufacturers including Daimler, Volvo, Navistar, Paccar and others, have already begun developing autonomous truck technology, for example. Waymo, an American autonomous driving technology development company has also installed self-driving technology in semi-trucks and plans to test on haulage routes in New Mexico and Texas. Tesla plans to deliver its first trucks in 2021. Pittsburgh-based Locomotion, an autonomous trucking technology company, expects to equip at least 1,120 Wilson Logistics tractors with its Autonomous Relay Convoy (ARC) technology starting in 2022.

In addition to autonomous driving, the trucking industry has the potential to reap many benefits from AI technology in accident prevention and safety, fuel efficiency, route optimization and workflow management.

Accident prevention and safety

One hundred percent autonomous driving may be a ways off, but already we’re seeing safety controls incorporated into trucks. For example, a Tesla computer will control its trucks’ semi-autonomous system for accelerating, brakes and steering — though drivers will still need to keep a hand on the wheel.

The Federal Motor Carrier Safety Administration (FMCSA) revised its HOS to provide more flexibility for drivers. However, many drivers still log 11 hours on the road each day — the potential for mistakes increases during the later period of a driving shift. AI-guided semi-autonomous trucks will help reduce safety hazards created from tired or distracted driving.

Fuel efficiency

One commercial truck can use over $70,000 of fuel each year. Multiply this amount by the number of trucks in a fleet, and you can see why trucking companies constantly search for strategies to improve fuel efficiency. AI-guided, self-driven trucks could cut fuel costs up to 15%, according to Plus (formerly A U.C. Berkeley Labor Center report estimated the industry could save $35 billion in fuel efficiency gains. Additionally, fuel monitoring and idle reporting features within AI-powered fleet management software platforms can help managers monitor fuel usage to reduce waste and costs.

Fleet management and route optimization

AI offers the perfect partner for fleet managers, increasing their effectiveness and helping to streamline and make processes more efficient. For example, these technologies can detect patterns humans might miss, increasing productivity by more accurately pinpointing which drivers to assign certain loads.

Route optimization benefits from AI, too. The technology streamlines route optimization, minimizing drive time and mileage by enabling fleet managers and drivers to find the most efficient, quickest order to schedule stops. AI can process traffic patterns and use algorithms to predict delays, even alerting dispatchers and managers earlier to facilitate load rescheduling or driver rerouting.

Drivers, fleet managers and customers benefit from AI-driven software capable of using real-time data about traffic, weather, and historical data on transit times to provide more accurate ETAs. Because AI constantly evolves, route optimization will become even more streamlined.

Workflow technology

The trucking industry has already benefited from many technology solutions designed to increase productivity and efficiency.

Drivers and fleets can use AI — together with cloud computing, machine learning (ML) and IoT — to move from paper management to digital management processes. Other technology has enabled fleets to identify customers affected by import tariffs, for example, and connect with those customers to develop mitigation strategies.

AI doesn’t just observe data or patterns. It’s capable of predicting potential scenarios based on past patterns. Workflow and fleet management software incorporating AI technology can help drivers and fleet managers with real-time navigation, data monitoring and predictive maintenance alerts. The future of AI within the trucking industry could include other businesses like capacity-as-a-service, predictive on-demand maintenance and shared insurance optimization.

AI’s future in the trucking industry

CB Insights reported that investors dedicated $2 billion to trucking tech startups in spring 2019. The transport and logistics sector represents $26 billion of total startup funding in the logistics industry.

Artificial intelligence has already begun to deliver on its promise to increase productivity, reliability, safety and sustainability within the trucking sector. While not a turnkey solution, AI technology relies on human knowledge to understand what to do. AI won’t replace people — it will reshape their roles and improve their work processes. AI is revolutionizing the trucking industry and promising to not just drive efficiency, but also better experiences for fleet management, drivers, customers and other critical stakeholders.


Avi Geller is the founder and CEO of Maven Machines. Since 2014, Avi has led Maven’s growth as an IoT platform that serves the transportation industry through real-time, mobile cloud enterprise software. Avi originally hails from Palo Alto, California, but started Maven in Pittsburgh, Pennsylvania due to the city’s impressive innovation and technology resources. Prior to founding Maven, he held international positions with SAP and contributed to the growth of several successful software companies and startups. Avi also has an engineering degree from MIT and an MBA from Northwestern University.

digital twinm market

Digital Twin Market: Top Impactful Trends Fostering the Industry Growth through 2026

The global digital twin market is expected to witness rapid development in the coming years, thanks to its increased adoption by enterprises to effectively manage various critical activities of their business. As the term suggests, it is considered as a digital counterpart of a real-time or physical machine or process. It can be a computer program that is quite useful for conducting virtual simulations of a physical product or process to understand and estimate its future performance.

Several governments across the world are showing their support towards the development of advanced production technologies in the form of favorable initiatives and policies. Digital twins are becoming quite popular among companies as they help them analyze the future performance of an object or process, thereby saving a lot of money, time and effort for the organization. For instance, ORE Catapult and James Fisher Asset Information Services Ltd., in April 2020, announced a strategic alliance to use digital twin technology for effective offshore wind management.

The top trends that will bolster the global digital twin industry are given below:

Use of advanced technologies will drive digital twin industry in Europe:

Europe’s digital twin market size is anticipated to go past the valuation of $9.5 billion during the forecast period of 2020-2026. The region is widely known for the creation and use of advanced technologies across different industries. Digital twin technology has picked up pace in recent years in several countries across Europe because of the rising need for virtual technologies and high-end analytical tools to help build future processes across industries.

GHENOVA Ingenieria launched its own digital twin center named GHENOVA 360 in May 2020. The launch will help in the creation and deployment of naval systems and has enabled the company to deliver solutions to military ship manufacturers.

The automotive industry will use digital twins to improve product performance:

Digital twin technology will find increased application in the European automotive industry. The automotive sector will use this technology to analyze the performance of vehicles and make desired changes. It will help companies make improvements in the overall design and efficiency of the vehicles as well. Advanced technologies like AI, IoT and IIoT are being increasingly adopted to continuously enhance the driving experience for the owners. The use of digital twin technology even helps predict potential risks in vehicles and provides solutions for the same.

Germany’s role in the European digital twin industry :

Germany is known for its use of advanced technologies and will play a key role in the development of the digital twin market in Europe. Digitization is taking place on a large scale across different sectors like healthcare in the country. This has prompted the development of digital twin solutions among many domestic companies.

Siemens AG announced a partnership with Atos SE to create digital twin services for the pharmaceutical sector. Various technologies like AI, IoT and IIoT are being used in digital twin processes to analyze the overall efficiency in the production of pharmaceutical products and make improvements accordingly. The use of this advanced technology has helped increase the overall reliability and quality of processes.

Improved design and performance demand in North America:

North America’s digital twin market is expected to become worth nearly $1.5 billion in valuation over the coming years. There has been a growing need for improving the design and performance of the products and services among the regional producers. In fact, the product design and development application held a share of nearly 50% in the regional digital twin market in 2019. The demand for detecting faults beforehand and making significant improvements in the design and performance of the product has stimulated the need for using digital twins.

This technology helps in saving a lot of money, time and efforts of companies by speeding up the designing procedures which ultimately helps in launching new products at a faster rate.

North America aerospace and defense sector uses digital twin:

The aerospace and defense sector in North America will increasingly adopt digital twin technology through 2026. One of the main reasons for this substantial rise in demand is the need to reduce casualties and increase the efficiency of military weapons. Digital twin technology helps in creating virtual models of weapons and other components to understand their current status.

The data received from real-time machinery helps the advanced technology in detecting potential faults in these weapons and even helps in predicting the exact time when maintenance will be required. The aircraft industry is using digital twins of real airplanes and feeding them with real-time data to improve the reliability of their functioning and reduce the overall cost of maintenance. They effectively help in enhancing the performance of the airplanes as well.

The rise in industry 4.0 practices will foster APAC digital twin market:

The Asian Pacific digital twin market will become worth more than $11 billion in valuation by 2026. Industry 4.0 is seeing rapid adoption across different sectors and is helping them become digital in many ways. The use of digital twin technology will enable industries in bridging the gap between the virtual and physical world and will even play an important role in enhancing overall efficiency and productivity. Toyota had, for example, had displayed its concept of futuristic warehouses with digital twin in April 2019, having intelligent pre-trained forklifts and lean logistics.

Higher focus on process support and services in Asia Pacific:

Digital twin technology solutions will find increased application in process support and services segment in Asia Pacific region. The Asia Pacific digital twin market share from the application is anticipated to grow at 35% CAGR throughout the mentioned forecast timeline. Processes of several industries can be improved with the help of digital twins; they can even be used to reduce the overall maintenance costs by predicting faults beforehand. These efforts will improve customer experience, reduce overhead costs incurred in repair and maintenance and optimize manpower use in the manufacturing processes.

Some of the prominent companies involved in providing digital twin technology solutions across the world are Oracle Corporation, IBM Corporation, Siemens AG, PTC Inc., SAS Institute Inc., Rockwell Automation, Schneider Electric and some others.