The best part is that the tool comes included with ClearGov’s platform, though the company’s CEO, Chris Bullock, said they “reserve the right” to charge for it in the future.

ClearGov has nearly 1,000 clients for which it can tap into past data and current figures to come up with future estimates.

“ClearGov’s FirstDraft feature uses advanced AI to generate an initial pass at several key sections of an agency’s budget book based on data that is fed automatically by the ClearGov budget cycle management platform,” Bullock said. “It is well-suited for fact-based content, such as explaining financial trends and changes. And, with a good starting point, Finance Directors or Budget Managers can quickly and easily edit the content to provide finer and more qualitative details in a fraction of the time it would have otherwise taken.”

According to Bullock, the training data used by FirstDraft so far spans three years, adding that ongoing feedback from clients could eventually lead to more years of data being included.

The included narratives can come in especially handy, as they put figures into context to help sell the budget to elected officials and citizens. This part, Bullock claims, is where AI gets a chance to shine.

“ChatGPT is great at writing a history of a city,” he said.

Municipalities participating in the beta testing of FirstDraft reported saving up to 25 percent of the time, or up to hundreds of hours.

Of course, tools like these are not meant to replace human input in budgeting or to put software in charge of how taxpayer money is spent. Instead, they are designed to make the process more efficient, especially when building a first draft of the budget.

That said, we should expect more AI participation in local and state governments.

“I believe this is the biggest tech innovation since the Internet,” Bullock said about AI in general.

ClearGov is a venture-backed firm that has raised $25.2M from investors, including RiverPark Ventures, LaunchCapital, Gutbrain Ventures, Frontier Growth, Hub Angels Investment Group, and Kepha Partners.

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In other words, the tool — which is basically a SaaS (Software-as-a-Service) for forest management — enables land managers to plan, prioritize, and execute fire prevention and forest health projects in months rather than years — including thinning hazardous timber, clearing fuels from roadsides, and conducting prescribed burns.

“We are facing concurrent, intertwined climate, wildfire, biodiversity, water, and health crises that cross jurisdictions and affect each and every one of us. Our future depends on how quickly we adapt, cooperate, and take action. With Land Tender, we can harness the best science, technology, and data to protect and restore forests and mitigate risk, quickly and at scale,” said Vibrant Planet CEO and Land Tender’s founder Allison Wolff, an early leader at Netflix and advisor to eBay, Google, Facebook, Drawdown, Conservation International, and other organizations on vision, strategy, culture change, and user-experience design over the past two decades.

Land Tender kicked off with a partnership with the Tahoe Fund, a nonprofit, and the California Tahoe Conservancy — helping land managers and owners, fire districts, scientists, local NGOs, and other stakeholders update Lake Tahoe’s community wildfire protection and forest health plan for the entirety of the lake’s 500-square-mile watershed basin. Simultaneously, a second partnership with the Truckee River Watershed Council created a comprehensive fire management plan for Lake Tahoe’s outlet, the Middle Truckee River Watershed, which serves as the main water source for the City of Reno and the Paiute Tribe in Northern Nevada.

“The Caldor Fire made it into the Lake Tahoe Basin, and we narrowly averted catastrophe, in part because of proactive fire prevention and forest health projects,” Tahoe Fund CEO Amy Berry said at the time of the Land Tender announcement. “Land Tender is a unique tool that can help communities like ours dramatically speed up the timeline of critical forest management projects — some of which have previously taken up to 10 years to plan and execute. This is exactly the type of project we started our ‘Smartest Forest Fund’ to help accomplish.”

In the last few years, we were witnessing intense, destructive, and costly wildfires driven by unnaturally dense forests, expanded development in fire-prone areas, and climate change — which has dried out vegetation, extended the fire season, and led to pest outbreaks that have killed millions of trees across the western U.S. In 2020 in California alone, wildfires resulted in the following:

• $3-4 trillion in ecosystem benefit losses at today’s market valuation, including carbon emissions and loss of carbon sequestration, water quality, recreation, and wood products;
• $63 billion in public health impacts;
• $2.3 billion in fire suppression costs; and
• 20 years of lost profitability for the insurance industry due to structural damage and loss.

Even as these cross-jurisdictional fire threats and costs escalate, land management planning and practices have remained largely the same — siloed, paper-based, and slow — with projects often taking up to 10 years to plan and execute. As governments and land managers scramble to adapt, Land Tender is a solid option to help catalyze a swift shift to proactive, technology-driven land management, backed by the best data and science, to reduce wildfire risks, restore watersheds, and protect habitat and biodiversity.

With Land Tender, parties across jurisdictions can collaborate and rapidly assess the current resilience of, and risk to, landscapes and communities, create and compare treatment scenarios at any scale, and make informed, ready-to-implement decisions in near real-time. This planning is done by utilizing high-resolution, three-dimensional datasets — including satellite imagery and aerial Light Detection and Ranging (LiDAR) technology — coupled with best-in-class infrastructure data to identify key inputs such as homes and utility infrastructure. Remote sensing, machine learning, and artificial intelligence also enable land managers to continuously monitor project progress, shift priorities and resources based on evolving conditions and threats, and gain insights on effective land management techniques to build community and wildland resilience.

Land Tender was designed with significant input from land managers, emergency responders, scientists, NGOs, and local and regional policy and decision-makers and built by a team of seasoned technology, ecology, and forest management leaders. It was first piloted in 2019 in collaboration with the North Yuba Forest Partnership to help bolster the resilience of a 275,000-acre, fire-prone watershed that serves as a key tributary to the Sacramento River Delta. The project, financed by Blue Forest’s Forest Resilience Bond, helped multiple landowners and collaborators assess current conditions and risks, define forest health and community protection objectives, and develop science- and data-informed treatment plans that the Yuba Water Agency and other funders could support.

Land Tender will generate a continuous pipeline of forest health and wildfire mitigation projects across the western U.S., supporting the development of a workforce of thousands to safeguard communities and restore western landscapes.

Vibrant Planet was started with $8 million in initial venture capital and philanthropic support from investors such as Earthshot Ventures, Facebook’s chief product officer Chris Cox, Netflix’s former chief product officer Neil Hunt, Elemental Excelerator, The Jeremy and Hannelore Grantham Environmental Trust, Halogen Ventures, and several private family foundations.

In June 2022, the company raised a $17 million seed round, adding more investors to the mix — including Ecosystem Integrity Fund (round lead), Valia Ventures, Cisco Foundation, and Day One Ventures, among others.

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In July 2022, the company announced UbiHub AP6, a triband Wi-Fi 6 Access Point that enables communities to enable public Wi-Fi. The platform integrates PoE, making it easy to support third-party equipment such as cameras and license plate readers. Also, at that time, they unveiled the UbiHub AP/AI, which adds dual 4K cameras, directional microphones, and a neural AI processor to the mix. The last mentioned is meant for street analytics and 15 days of video storage.

Both UbiHub solutions are compatible with more than 360 million streetlights worldwide and can be installed in seconds plugging into the existing streetlight photocell socket.

The idea to integrate multiple functions into one easy-to-install platform is sound, and according to Northeast Group – this approach reduces the total cost of ownership by 42% when compared to conventional multi-vendor solutions.

“Our UbiHub is the ‘Swiss Army Knife’ of intelligent infrastructure for cities and utilities,” Ian Aaron, CEO of Ubicquia, said in a press release. “Whether you need to scale the deployment of cameras and license plate readers across multiple vendors or simply expand broadband in commercial areas and parks, UniHub is the only multi-function product in the market that installs in seconds and delivers data in minutes.”

UniHub platforms enable cities and law enforcement to cost-effectively scale and transform their existing streetlight infrastructure into a network of connected digital assets. Specifically, the solutions can help:

• Enable faster, evidence-based crime detection, investigation, and deterrence;
• Reduce traffic congestion, improve pedestrian safety and increase bicycle lane utilization;
• Expand city broadband deployments in commercial areas and parks.

Like other Ubicquia products, UniHub is managed and monitored with UbiVu, Ubicquia’s cloud visualization and analytics management system. In addition, UbiVu supports APIs that integrate with leading third-party video management systems, evidence clearance platforms, and police real-time crime centers.

The City of West Hollywood in California is among municipalities that have deployed UniHub, and are now collecting all kinds of data for their future planning development needs. Another client is the County of Hawai’i, which is using the solution to enable equitable internet access and close the digital divide throughout Hawai’i Island, and so has the City of Ontario, which deployed 12,500 UbiCells for smart lighting analytics and energy savings.

With more than 360 million street lights globally, these vertical assets are increasingly viewed by cities as critical enablers for new smart city applications, according to Ben Gardner, President of market intelligence firm Northeast Group. “Starting with well proven energy and cost savings derived from intelligent lighting controls, new solutions are now evolving to boost public safety, broadband access and the automation of municipal functions,” he added.

Aside from UniHub, Ubicquia also has other products in its portfolio, including UbiCell, which enables smart streetlight control; UbiMetro, a streetlight small cell that accelerates 4G and 5G network deployments; and UbiSmart AQM+, a sensor that monitors a city’s air quality index, noise levels, and environmental data.

The post A solution helps cities deploy public Wi-Fi and cameras for traffic analytics and public safety appeared first on Sustainable Avenue.

The pilot project involves a smartphone app using which citizens can control the city’s street lighting, like brightening the lights in a dark storm or dimming them when the days get longer. This isn’t only cool in a gimmicky way but could also reduce the city’s energy consumption.

The story comes from Bad Hersfeld, the 30,000-population spa town in Germany that has teamed up with [ui!] Urban Lighting Innovations — which constructs and modernizes street lighting systems for smart cities. Other project supporters include Microsoft, Deutsche Bank, and the Berlin Institute of Technology.

The system uses artificial intelligence (AI) and works even without interference from residents, relying on sensors to collect data on traffic, ambient light and weather conditions to adapt the lighting accordingly. For example, lights are dimmed on empty streets, causing less light pollution.

These are all energy-efficient LED lights that have a much longer lifespan than normal streetlights and, with this adaptive use of dimming and brightening, can actually save a city like Bad Hersfeld up to 90% of its energy consumption while significantly reducing its carbon footprint.

This is fairly important because cities are major sources of CO2 emissions, consuming 78% of the world’s energy and producing more than 60% of greenhouse gas emissions. Street lighting accounts for the largest energy costs in a public budget of many cities — in European cities, up to 50%.

“Cities need individual, decentralized solutions for street lighting if they want to move to a more sustainable model,” explained Lutz Heuser, [ui!] CEO. “Light in public spaces should be energy-efficient, safe for traffic, and it should meet climate protection goals but also the needs of citizens. It can be a challenging proposition, but it’s one we set out to meet with Smart-City-as-a-Service.”

The project has been awarded the Smart 50 Award by the US-based Smart City organization, and Bad Hersfeld is the only German city — and one out of only two European cities — to receive the award this year. Heuser believes that if every city in Germany followed Bad Hersfeld’s lead, the country could achieve the Intergovernmental Panel on Climate Change 2050 net-zero target. “It has been proven and it works,” he said.

In phase two of the project, the citizens of Bad Hersfeld are taking control of their street lighting. Using a mobile app, they can dim lights that, for example, reflect off wet streets, causing a safety hazard, or shine directly into bedrooms.

Finally, to make this sort of smart lighting available to more cities throughout Europe and elsewhere, [ui!] created the light-as-a-service model. This means that a city can pay for lighting annually for the term of the contract without paying a hefty fee upfront.

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To tackle this problem, researchers from the University of Technology Sydney have developed new “intelligent compaction” technology, which can be integrated into a road roller to assess in real-time the quality of road base compaction. As a result, it can reduce potholes and maintenance costs, leading to safer and more resilient roads.

Said technology uses an innovative machine-learning technique to process data from a sensor attached to a construction roller. The study was led by Associate Professor Behzad Fatahi, head of geotechnical and transport engineering, together with Professor Hadi Kahbbaz, Dr Di Wu, and Ph.D. student Zhengheng Xu.

“We have developed an advanced computer model that incorporates machine learning and big data from construction sites to predict the stiffness of compacted soil with a high degree of accuracy in a fraction of a second, so roller operators can make adjustments,” said Associate Professor Fatahi.

Generally speaking, roads are made up of three or more layers, which are rolled and compacted. The subgrade layer is usually soil, followed by natural materials like crushed rock and then asphalt or concrete on top. The variable nature of soil and moisture conditions can result in under or over-compacted material.

The adopted machine learning method incorporating Gaussian Kernel and Generalised Gegenbauer Kernel functions can reasonably predict the double-layered soil modulus during roller compaction. Researchers conducted additional analyses to observe the proper training size and number of iterations to achieve real-time quality control to be used by site engineers.

“Like Goldilocks, the compaction needs to be ‘just right’ to provide the correct structural integrity and strength. Over-compaction can break down the material and change its composition, and under-compaction can lead to uneven settlement,” added Associate Professor Fatahi. “A well-compacted multi-layer road base provides a stable foundation and increases the capacity of a road to bear heavy loads. Trucks can weigh up to 40 tonnes, so a poor quality base can quickly lead to cracks and weak spots in the asphalt surface.”

Researchers have published their paper in the peer-reviewed journal Engineering Structures, suggesting the application of this technology could help build longer-lasting roads that can better withstand severe weather conditions.

Now, the team is looking to test the technology onsite for various ground and roller conditions for road, railway and dam construction projects. Also, they want to explore techniques to measure the density and moisture content of the compacted soil in real time during construction.

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Derq, an award-winning MIT spin-off, is looking to address burning needs in pedestrian and cyclist safety with a novel, AI-based solution. It has already been demonstrated in Florida during the first half of 2022 — in collaboration with Control Technologies, Danlaw, and CēVē.

At that time, Derq showed its ability to prevent collisions between drivers, pedestrians, and cyclists using a variety of approaches — including connected vehicle messages, flashing pedestrian signs, actuating traffic signals, and smartphone alerts. The solution also reports advanced safety insights, helping agencies better understand and improve road safety performance.

Derq’s real-time perception and connectivity AI platform ingests and aggregates data from various sources, such as traffic cameras, signal controllers, connected vehicles, smartphone apps, and other cloud-based services.

“Over the years, we’ve partnered with various leading ITS technology providers across the US and have deployed thousands of intelligent sensor-based solutions,” said Pete Ganci, VP at Control Technologies, “the Derq AI Platform is the only one on the market that we have seen capable of powering a fully integrated pedestrian and cyclist safety solution on the market, allowing vehicles, pedestrians, and cyclists to communicate with each other and the infrastructure, while also delivering real-time adaptive traffic management and reporting advanced safety analytics, such as pedestrian compliance issues and near-miss reporting.”

The Derq solution is able to detect, track, and predict the intent of pedestrians, cyclists, and vehicles as they approach crossings in real time through its AI-powered computer vision algorithms. By fusing this detection data with data ingested from traffic signal controllers, connected car messages (C-V2X), and smartphone apps – it can generate real-time alerts and set off decisions to protect pedestrians and cyclists from hazardous conflicts with vehicles.

“Driver, pedestrian, and cyclist safety are paramount to everything we do,” said Karl Jeanbart, COO of Derq. “Our proven third-party-tested solution can be deployed immediately to alert drivers, pedestrians, and cyclists about potential hazards in their environment, avoid collisions, and save lives.”

During the mentioned demonstration in Florida, several use cases were highlighted, including:

• Placing a call within a traffic signal controller to activate the desired pedestrian phase by utilizing the data generated from the fusion of passive pedestrian detection and a smartphone app.
• Activating flashing pedestrian signs (such as RRFBs) at mid-clock crossings for an approaching pedestrian by utilizing the data generated from the fusion of passive pedestrian detection and a smartphone app.
• Alerting approaching vehicles both audibly and visually of pedestrian or cyclist presence based upon a potential conflict prediction made possible by the broadcasting of C-V2X messages such as Basic Safety Messages (BSM) and Personal Safety Messages (PSM) generated by the fusion of passive pedestrian detection and a smartphone app.
• Alerting pedestrians and cyclists using a smartphone app at crossings of approaching vehicles based upon a potential conflict prediction made possible by the fusion of advanced vehicle detection and C-V2X messages (BSMs) broadcasted by the vehicle.

In addition, the platform also generated an array of real-time safety and traffic insights, such as the detection of traffic violations, pedestrian compliance issues, and road-user conflict (near-miss) data — providing up-to-date, granular data to enable the analysis of safety issues.

For the demonstration, Danlaw provided its RouteLink C-V2X Roadside Unit and AutoLink C-V2X Onboard Unit for this demonstration; while CēVē chipped in with iOS and Android apps that connect drivers, pedestrians, and cyclists to transportation infrastructure. Ultra Engineering and Precision Contracting Services (PCS) also supported the technology team during the demonstration.

The post This company’s tech aims to reduce pedestrian and cyclist fatalities appeared first on Sustainable Avenue.

To address these challenges, in May 2020 – Zurich, Switzerland-based Hitachi Energy launched Lumada Inspection Insights, its end-to-end portfolio of digital solutions for the inspection, monitoring, and optimization of critical assets. These are some sophisticated solutions, relying on AI and machine learning (ML) to analyze a wide spectrum of image types, assets and risks.

One of them, Hitachi Vegetation Manager, the company describes as “the first of its kind, closed-loop vegetation resource planning solution that leverages artificial intelligence and advanced analytics to improve the accuracy and effectiveness of an organization’s vegetation job activities and planning efforts.”

The solution, which uses algorithms developed at one of the company’s R&D centers in Japan, takes images of trees and forests from a variety of sources — including photo, video, and imagery from industry-leading Maxar satellites. By combining the images with climate, ecosystem and cut plan data as well as machine learning algorithms, Hitachi Vegetation Manager provides utilities with grid-wide visibility and better insights so that organizations can optimize decision-making.

“With satellites remotely capturing images and AI analyzing them, we can better optimize and plan for addressing areas of concern,” Bryan Friehauf, SVP of enterprise software solutions at Hitachi Energy, told VentureBeat. “This will also reduce the cost and emissions of the management program by minimizing truck and helicopter trips, and ultimately minimize outages and fires caused by vegetation.”

According to John Villali, research director at IDC Energy Insights, inspection, planning and monitoring are “among the most critical tasks utilities undertake to maintain grid reliability and resiliency. To that end, Hitachi Energy’s solution aims to empower utilities to improve decision making, optimize operations and “as a result, achieve their reliability, safety and sustainability goals.”

Overall, the Hitachi Vegetation Manager gives utilities and government agencies a very accurate prognostic on how the vegetation is growing and this is important for anyone who has to manage vegetation around their linear assets. In other words, some cities could use tech like this.

The post This high-tech solution uses AI to analyze trees and prevent wildfires appeared first on Sustainable Avenue.

The process starts with a 3D scan of a house, after which Ecoworks makes wood panels of identical shape and scale to be attached to the outside. As a result, even the most inefficient buildings can be turned into net-energy producers.

In that sense, these panels come with built-in solar panels and insulation. They are also reportedly easy to set up, with the company claiming they could be installed in as little as 20 minutes. A full building conversion, including replacing fossil-fuel-powered heat, can be done in a few weeks.

Even the wood these panels use is eco-friendly as it has been harvested only after achieving optimal carbon capture.

In a demonstration, an apartment block from the 1930s that used 450 kilowatt-hours per square meter of space was equipped with Ecoworks panels while the company monitored the changes in energy consumption.

After the installation, it became so inexpensive to heat, cool, and power, that the solar panels on the roof made this a carbon-negative building, whereas before it was listed as one of the least efficient in the whole nation.

Ecoworks is using artificial intelligence to identify the buildings that will be best suited for its technology. And it will have a ton of work ahead, with reports suggesting that in Germany alone – there are 30 million buildings that are in need of renovation over the next five years to meet prescribed climate targets.

The post This company makes prefab facades that make old buildings energy efficient appeared first on Sustainable Avenue.

In March 2022, a new programme called H2A was launched in Leicester, UK — relying on artificial intelligence to provide more personalized weight loss support for people in a bid to tackle obesity and its related risks. The team is creating a software tool that takes into account factors such as demographics, location, and social and environmental influences. The initiative will also inform wider policies and localized strategies to reduce barriers to healthy lifestyles.

The H2A programme is being delivered by De Montfort University Leicester (DMU) and Leicester City Council, bringing together experts in AI, sports, psychology, nutrition and social care. It aims to help adults in Leicester, half of which are overweight or obese, as well as children for whom the obesity is higher than national levels.

Specifically, H2A aims to increase the numbers of children taking part in school sports and support the development of neighborhood programmes to encourage more active lifestyles. By analyzing data, the researchers are also looking to find “hidden trends” across Leicester.

“Our vision is to co-create with local communities and stakeholders to make physical activity and a healthy diet easier and promote healthy weight across our local population,” said Bertha Ochieng, Professor of Integrated Health and Social Care at DMU and lead for the project. “During the project, we will develop an interactive tool to allow the study to target the areas and communities most in need and support the local public health practitioners’ whole systems approach to promoting healthy weight across the lifespan.”

The H2A team has access to datasets including health deprivation statistics, pollution levels, physical activity, health authority information, average weight, sports and wellbeing data broken down by postcode and Sports England studies. It includes hundreds of thousands of data points with multitudes of features within them.

The project is at an early stage but it could show trends related to age, employment status, air pollution or consumption of takeaway food, for example. The tool could also inform the placement and promotion of services such as shared bikes.

An AI model that can predict the minimum changes needed in an individual’s lifestyle will be incorporated into the digital app and suggest so-called “nudges” to improve one’s wellbeing.

The H2A programme is the latest project in DMU’s Local+ programme, a joint scheme through which academics become consultants for the authority, applying their own and others’ research into key projects.

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Grycle is a waste management system that uses AI to manage multiple materials at the same time, recognizing and separating them all in one step. For instance, a plastic bottle will be separated into three different parts — the body of the bottle, the cap and the label — and treated accordingly. The software running Grycle will recognize and sort each of these automatically.

The process starts by shredding all the materials, after which the small parts are put through an electromechanical filter to separate the different components. Then, the spectrometer kicks in, analyzing these small components before depositing them into a bin containing only one type of material. From there, each material is processed into a composite pellet that can easily be reused by different industries to make new materials.

The best part is that the machine itself is powered by solar power (PV) and is compact enough to be portable.

“Grycle is special because in recent years there has been an increased awareness of the need for a radical change in the human relationship with the environment on a global scale,” Daniele Pes explained. “However, where everyone was talking about the problem, Grycle has been perceived as a sustainable solution, enabling a change in dramatically reducing human impact. The difference between talking about something and actually doing something is too wide, and we realized that, and did something about it.”

Over 2.1 billion tons of unsorted waste is produced globally every year, and by 2050 it is estimated there will be a 70% increase in this global waste mountain. Even worse is the fact that treating solid waste produces 1.6 billion tons of CO2 each year, representing one-fifth of global emissions. Machines like Grycle could help make a dent.

As of January 2022, the project is still in the prototype stage and the company is looking for investors to help scale up and enter the mainstream market.

The post This machine provides for an AI-enabled, waste-sorting process appeared first on Sustainable Avenue.