Understanding the future of smart cities through data science


The above-featured image is for illustration and is credit to White & Case

Understanding the future of smart cities through data science

By  in Data Science Central

The concept of smart cities is to use advanced technologies to minimize traffic congestion, manage waste better, and improve the quality of life for people. Data science will play a critical role in managing intelligent cities. It will help avail insights to help city managers make data-driven decisions. Big data will offer a unique opportunity for running sustainable and livable cities.

City dwellers will benefit from minimum energy use, less pollution, and better air quality. The development of the cities faces different challenges such as competition of resources and data privacy issues. Urban managers and dwellers will use various AI-driven techniques, systems, and processes to get real-time analysis and reports to understand actual happenings.

Understanding the future of smart cities through data science

Image Credit – Pexels

How data science will help intelligent cities become smarter and more efficient

Advancing data analytics will offer unprecedented chances for urban environments to increase sustainability, resilience, and livability. Leveraging data-based insights will be critical when making informed decisions. City management authorities will rely on data to improve traffic flow, manage energy distribution and use, waste, and make plans for smarter infrastructure.

Data analytics in smart cities will provide quick and dependable ways for analyzing raw data to help understand the real-time dynamics of cities. It will be useful in enabling planning and developing new adaptations for challenges. Efficiency is important in advanced cities. Big data will help minimize pollution to the environment and increase the quality of air. Urban management will effectively supply the right amount of energy required to keep systems running and buildings livable.

As smart cities develop more, society needs to address a variety of data privacy and security risks.  Resolving them in a smart security environment needs a holistic approach. WIFI connection will play a major role in intelligent cities but various WIFI security issues might arise. One of them is that this network is blocking encrypted DNS traffic, especially when a user gets a new WIFI connection. This is a common issue that affects network security on Mac.

If you fail to resolve privacy warning in Mac you could compromise your data and privacy. One of the ways to resolve this network blocking encrypted DNS traffic is to restart your gadget, reconnect your WIFI, or update your gadget. DNS blocking happens when a company tries to prevent DNS encryption so that it can snoop on your data. That is when your gadget’s OS displays the message network is blocking encrypted DNS traffic. You might want to use a VPN, reconnect your internet, or change your connection password to resolve this issue.

Image Credit- Pexels

Benefits of using data science in smart cities

The effects of climate change are impacting every sector of society. Globally, societies are experiencing challenges such as:

●       Hotter temperatures

●       Poorer food production

●       Diminishing human, animal, and plant health

●       More species going extinct

●       Increasing poverty, droughts, and live threatening storms

One of the aims of developing intelligent cities is to find solutions to these challenges. Scientists are finding ways to minimize the production of CO2 and improve human life. The aim of data-driven smart cities is not only to minimize CO2 emissions but also to provide a variety of benefits to urban dwellers.

Produce more energy and use less. Smart city technologies aim to save more energy in a wide variety of ways.

Ensure there is cleaner air for urban dwellers. Smart urban planning authorities will use technologies to measure air quality and understand sources of pollution.

Enhanced transportation. City data analysis and systems in smart cities aim to optimize mobility in urban places. Data will help pinpoint challenges in transportation systems, minimize congestion, and provide real-time traffic updates.

Enhanced waste management. AI-driven city management will help gather data across ecosystems for waste recycling, repair, and reuse. Big data will help reduce waste production and management of waste delivery channels.

Enhanced public safety and quality of life. Data privacy in smart cities will help security teams keep an eye on real-time happenings across streets and buildings using AI-driven cameras.

Image Credit – Pexels

Challenges that cities face in implementing data-driven solutions

Terabytes of data can be generated daily which is important for improving efficiency in smart cities. However, big data poses a major storage challenge to both City management and dwellers. The data generation, processing, and storage systems are prone to cyberattacks.

International and local policies for data privacy and sharing keep changing which poses a major challenge to companies, governments, and individuals. As urban technology improves, legislation needs to change. The current laws are full of loopholes that hinder the swift implementation of smart city policies. There needs to be greater connectivity and efficiency but intelligent use of big data is currently lacking.


The realization of smart cities is approaching fast as societies become more intertwined with urban technology. Big data is playing a major role in speeding up the pace and improving efficiency, and quality of life. Still, there are several drawbacks that the current generation has to deal with. They have to address issues of cybersecurity, data privacy, CO2 emissions, legislation, and economic improvements of the people.


Technology is Breaking New Ground in the Construction Industry

The above-featured image is for illustration and is credit to World Construction Today.

How Technology is Breaking New Ground in the Construction Industry

MELBOURNE, VICTORIA, AUSTRALIA, August 4, 2023/EINPresswire.com/ — The construction industry is undergoing a significant revolution, driven by groundbreaking technological advancements. As professionals in engineering and construction embrace digital transformation, the concept of ‘Construtech’ is reshaping traditional construction techniques and changing the way the industry thinks about its data.

Technological Trends Driving the Future of Construction:

The construction industry is witnessing a rapid shift towards technological innovations that are transforming how projects are planned, designed, and executed. Some of the key technological trends driving the future of construction include:

Construction Management Software:

Construction management software is at the forefront of technological innovations in the construction industry. This advanced software suite streamlines project management processes, allowing construction teams to collaborate seamlessly, manage resources effectively, and monitor project progress in real-time. With features like document management, task tracking, and cost control, construction management software enhances efficiency and productivity throughout the project lifecycle.

Project Management Software for Construction:

Project management software tailored for the construction sector has become an essential tool for managing complex projects. From project planning to scheduling and budgeting, this software empowers construction professionals to optimise project timelines and resources efficiently. Real-time data and analytics enable proactive decision-making, ensuring projects are delivered on time and within budget.

Vendor Management Systems:

Efficient vendor management is crucial for construction companies, and technology is providing solutions to streamline the process. Vendor management systems offer tools to manage supplier information, track performance, and ensure compliance with industry regulations. Vendor management software simplifies the procurement process, ensuring a reliable supply chain for construction projects.

Accounts Payable Software:

Automating accounts payable processes has become a game-changer in the construction industry. Accounts payable software eliminates manual tasks, reduces processing time, and minimises the risk of errors. With streamlined invoice approvals and payment processing, construction companies can improve financial efficiency and cash flow management.

Call Forwarding Software:

Communication is the lifeline of any construction project, and call-forwarding software enhances connectivity and accessibility. This technology allows construction professionals oversight on critical pieces of communication that can otherwise go unchecked. Whether on-site or in the office, call-forwarding software keeps teams connected, promoting seamless communication and collaboration, and helps keeps budgets in check.

How Evolve Construction Management Software is Useful:

Among the pioneers of Construtech, the Evolve Construction Management Software Suite stands out as a game-changing solution for the construction industry in Australia. With a focus on efficiency, productivity, and seamless project management, Evolve Construction Management Software offers comprehensive features, including:

Project Planning and Scheduling: Effortlessly plan and schedule construction projects, allocate resources, and track progress in real-time.

Document Management: Centralise project documents, contracts, and permits for easy access and efficient collaboration.

Cost Control and Budgeting: Monitor project costs, manage budgets, and track expenses to ensure projects stay within financial constraints.

Task Management: Streamline tasks and assign responsibilities, keeping construction teams organised and on track.

Mobile Accessibility: Access project data and updates on the go with mobile compatibility, ensuring effective communication and decision-making even in the field.

“As technology continues to break new ground in the construction industry, we are proud to offer cutting-edge solutions like Evolve Construction Management Software to our clients,” says Bill Kennedy, CEO of Evolve Construction Management. “With the adoption of ‘Construtech’, we aim to empower construction professionals, enhance project efficiency, and drive success in the ever-evolving construction landscape.”

The rise of Construtech signifies an exciting era of innovation and transformation in the construction industry. As professionals embrace these technological trends, the future of construction promises to be more efficient, sustainable, and dynamic.

About Evolve Construction Management:

Evolve Construction Management is a leading construction solutions provider committed to leveraging technology for superior project management and construction excellence. With a focus on client satisfaction and innovation, Evolve Construction Management is at the forefront of driving the construction industry into the digital age.

Bill Kennedy
Evolve Construction Management email



Exploring the Intersection of AI and Sustainable Architecture


The image above is for illustration and credit to GettyImages.

AI and the Built Environment: The Next Generation of Design Solutions

Exploring the Intersection of AI and Sustainable Architecture

Artificial intelligence (AI) has been making waves in various industries, and it’s no surprise that it’s now finding its way into the world of architecture and design. As we strive to create more sustainable and efficient buildings, AI has the potential to revolutionize the way we approach the built environment. By exploring the intersection of AI and sustainable architecture, we can unlock the next generation of design solutions that will help shape the future of our cities and communities.

One of the most significant ways AI can contribute to sustainable architecture is through the optimization of building design. Traditionally, architects and engineers have relied on their experience and intuition to create energy-efficient buildings. However, AI algorithms can analyze vast amounts of data and consider numerous design variables to identify the most sustainable and cost-effective solutions. This data-driven approach can lead to more innovative designs that minimize energy consumption, reduce waste, and lower the overall environmental impact of buildings.

For example, AI can be used to optimize the orientation, shape, and size of a building to maximize natural light and minimize heat gain. This can result in a more comfortable indoor environment while reducing the need for artificial lighting and air conditioning. Similarly, AI can help architects select the most appropriate materials and construction techniques to improve a building’s thermal performance and reduce its carbon footprint.

Another area where AI can make a significant impact is in the design of urban environments. As cities continue to grow and urban populations increase, there is a pressing need to create more sustainable and livable urban spaces. AI can be used to analyze complex urban systems and identify the most effective strategies for improving air quality, reducing traffic congestion, and promoting walkability and public transportation. By using AI to inform urban planning decisions, we can create more sustainable and resilient cities that are better equipped to face the challenges of the future.

In addition to optimizing design, AI can also play a crucial role in the ongoing management and maintenance of buildings. By integrating AI with building management systems, it’s possible to monitor and analyze the performance of a building in real-time. This can help identify inefficiencies and potential issues before they become significant problems, allowing for more proactive maintenance and reducing the overall environmental impact of a building throughout its lifecycle.

Furthermore, AI can be used to create more responsive and adaptive buildings that can adjust to changing conditions and occupant needs. For instance, AI-powered systems can learn from occupants’ behavior and preferences to optimize lighting, heating, and cooling, resulting in a more comfortable and energy-efficient environment. This level of personalization can not only improve the overall user experience but also contribute to greater sustainability by reducing energy waste.

As we continue to explore the intersection of AI and sustainable architecture, it’s essential to consider the ethical implications of these emerging technologies. While AI has the potential to revolutionize the built environment, it’s crucial to ensure that these advancements are used responsibly and equitably. This includes addressing issues related to data privacy, algorithmic bias, and the potential displacement of human workers in the design and construction process.

In conclusion, AI offers a wealth of opportunities for creating more sustainable and efficient buildings and urban environments. By harnessing the power of AI, architects, engineers, and urban planners can develop innovative design solutions that minimize environmental impact, improve building performance, and enhance the overall quality of life for occupants. As we continue to explore the intersection of AI and sustainable architecture, we can look forward to a future where our built environment is smarter, more resilient, and more sustainable than ever before.





Is generative AI bad for the environment?


Is generative AI bad for the environment? A computer scientist explains the carbon footprint of ChatGPT and its cousins

By Kate Saenko, Boston University

The image above is on The Generative AI Race Has a Dirty Secret, credit to WIRED

AI chatbots and image generators run on thousands of computers housed in data centers like this Google facility in Oregon.
Tony Webster/Wikimedia, CC BY-SA

Generative AI is the hot new technology behind chatbots and image generators. But how hot is it making the planet?

As an AI researcher, I often worry about the energy costs of building artificial intelligence models. The more powerful the AI, the more energy it takes. What does the emergence of increasingly more powerful generative AI models mean for society’s future carbon footprint?

“Generative” refers to the ability of an AI algorithm to produce complex data. The alternative is “discriminative” AI, which chooses between a fixed number of options and produces just a single number. An example of a discriminative output is choosing whether to approve a loan application.

Generative AI can create much more complex outputs, such as a sentence, a paragraph, an image or even a short video. It has long been used in applications like smart speakers to generate audio responses, or in autocomplete to suggest a search query. However, it only recently gained the ability to generate humanlike language and realistic photos.

Using more power than ever

The exact energy cost of a single AI model is difficult to estimate, and includes the energy used to manufacture the computing equipment, create the model and use the model in production. In 2019, researchers found that creating a generative AI model called BERT with 110 million parameters consumed the energy of a round-trip transcontinental flight for one person. The number of parameters refers to the size of the model, with larger models generally being more skilled. Researchers estimated that creating the much larger GPT-3, which has 175 billion parameters, consumed 1,287 megawatt hours of electricity and generated 552 tons of carbon dioxide equivalent, the equivalent of 123 gasoline-powered passenger vehicles driven for one year. And that’s just for getting the model ready to launch, before any consumers start using it.

Size is not the only predictor of carbon emissions. The open-access BLOOM model, developed by the BigScience project in France, is similar in size to GPT-3 but has a much lower carbon footprint, consuming 433 MWh of electricity in generating 30 tons of CO2eq. A study by Google found that for the same size, using a more efficient model architecture and processor and a greener data center can reduce the carbon footprint by 100 to 1,000 times.

Larger models do use more energy during their deployment. There is limited data on the carbon footprint of a single generative AI query, but some industry figures estimate it to be four to five times higher than that of a search engine query. As chatbots and image generators become more popular, and as Google and Microsoft incorporate AI language models into their search engines, the number of queries they receive each day could grow exponentially.

AI chatbots, search engines and image generators are rapidly going mainstream, adding to AI’s carbon footprint.
AP Photo/Steve Helber

AI bots for search

A few years ago, not many people outside of research labs were using models like BERT or GPT. That changed on Nov. 30, 2022, when OpenAI released ChatGPT. According to the latest available data, ChatGPT had over 1.5 billion visits in March 2023. Microsoft incorporated ChatGPT into its search engine, Bing, and made it available to everyone on May 4, 2023. If chatbots become as popular as search engines, the energy costs of deploying the AIs could really add up. But AI assistants have many more uses than just search, such as writing documents, solving math problems and creating marketing campaigns.

Another problem is that AI models need to be continually updated. For example, ChatGPT was only trained on data from up to 2021, so it does not know about anything that happened since then. The carbon footprint of creating ChatGPT isn’t public information, but it is likely much higher than that of GPT-3. If it had to be recreated on a regular basis to update its knowledge, the energy costs would grow even larger.

One upside is that asking a chatbot can be a more direct way to get information than using a search engine. Instead of getting a page full of links, you get a direct answer as you would from a human, assuming issues of accuracy are mitigated. Getting to the information quicker could potentially offset the increased energy use compared to a search engine.

Ways forward

The future is hard to predict, but large generative AI models are here to stay, and people will probably increasingly turn to them for information. For example, if a student needs help solving a math problem now, they ask a tutor or a friend, or consult a textbook. In the future, they will probably ask a chatbot. The same goes for other expert knowledge such as legal advice or medical expertise.

While a single large AI model is not going to ruin the environment, if a thousand companies develop slightly different AI bots for different purposes, each used by millions of customers, the energy use could become an issue. More research is needed to make generative AI more efficient. The good news is that AI can run on renewable energy. By bringing the computation to where green energy is more abundant, or scheduling computation for times of day when renewable energy is more available, emissions can be reduced by a factor of 30 to 40, compared to using a grid dominated by fossil fuels.

Finally, societal pressure may be helpful to encourage companies and research labs to publish the carbon footprints of their AI models, as some already do. In the future, perhaps consumers could even use this information to choose a “greener” chatbot.

Kate Saenko, Associate Professor of Computer Science, Boston University

This article is republished from The Conversation under a Creative Commons license. Read the original article.


Digitisation could turn electricity into a worldwide network


Digitisation could turn electricity into a worldwide network – tech expert

Referencing the Rubik’s cube, Edwin Diender, Chief Innovation Officer: Global Electric Power Digitalisation Business Unit, Huawei Technologies, Thailand, said each cube represents something or someone.

He was speaking on the second day of Enlit Africa 2023, focusing on the theme, Find the Right Technologies to Power the Global Energy Transition.

A cube that contains all the requisite components has the potential to link up the worldwide web of energy, he said.

“It is energy powering the construction of intelligent cities.

“The digital journey is passing phases. It’s a journey that follows programmes and initiatives and brought together as pieces through universal infrastructure.”

Diender said the conversion of analogue to digital is the first step to digitisation. In the energy sector, for example, analogue meters are replaced by smart meters, an item that is digitised and may be “the first step on this journey.”

The next step involves different building blocks that are brought together in a smart system that’s intelligent. This cube connects to many other cubes by a digital framework.

Diender said Huawei is looking at other forms of infrastructure, including electric power digitisation.

This would encompass finding the right technologies to help drive the digital journey for the energy industry.

Harnessing electricity transmission through digitisation

The company wants to “grab opportunities” like a software defined grid, intelligent power plant and green intelligent energy solutions. It wants to bridge industry requirements with digital technologies and finding the right technologies for industrial scenarios.

“The digital journey is a collaborative journey. We are working closely with customers worldwide in the electric power industry.”

He also cited technology solutions that can be used to protect power infrastructure – like an intelligent substation inspection system. Diender said the award-winning Yancheng Industrial Park was an example of Huawei looking at digital energy solutions.

The Yancheng Park project was jointly developed by the company and the Yancheng Power Supply Company, a subsidiary of the State Grid Corporation of China.

“The project uses the triple-dimensional model for energy transformation, decarbonisation, and digital transformation.

“By focusing on the three scenarios of smart energy management, carbon management, and campus management, this project delivers real-time monitoring of energy equipment, strong carbon emission management, intelligent and convenient access control management, and intelligent and coordinated micro-grid control.

“The campus is powered by complementary energy sources and integrates its energy consumption system with on-campus terminals.

“The project is a showcase of an intelligent and low-carbon campus that contributes to a green, low-carbon, safe, and efficient modern energy system.”