It's vital that businesses monitor their data models in real-time and lookout for anomalies that could cause problems. If a product is suddenly selling at 10 times the normal rate a human might need to step in and amend the processes in place. Businesses need to be proactive about which machine learning models and which input variables within the models are most sensitive to extreme events. Anything that depends on human behaviour--from electricity demand to shopping--will be affected by major events. The business's data scientists should sit down with subject-matter experts and stress-test a system in simulation: What items might customers want in a crisis?
New carbon emission tracking technology will quantify emissions of greenhouse gas, holding the energy industry accountable for its CO2 output. Backed by Google, this cutting-edge initiative will be known as Climate TRACE (Tracking Real-Time Atmospheric Carbon Emissions). Advanced AI and machine learning now make it possible to trace greenhouse gas (GHG) emissions from factories, power plants and more. By using image processing algorithms to detect carbon emissions from power plants, AI technology makes use of the growing global satellite network to develop a more comprehensive global database of power plant activity. Because most countries self-report emissions and manually compile results, scientists often rely on data that is several years out of date.
For the energy industry, securing the grid is mission-critical. Increasingly, too, securing devices that lie beyond the centralized grid -- at the edge, so to speak -- is also critical as well as a moving target. Zero-trust cybersecurity, 5G connectivity and machine learning, though, may ultimately help this "smart grid," as this connected energy grid is known, become more resilient in the face of attacks. While the shift toward sustainable energy could help secure a better future for the planet and reduce carbon footprint, the smart grid -- fueled by connected things, microgrids and so on -- creates two-way, risky data flows that add complexity to an already antiquated energy grid. Smart grid technologies can balance peak demand, flatten the load curve and make energy generation sources more efficient, said Brian Crow, Sensus' vice president of analytic solutions, in a recent article on the role of IoT in utilities.
StartX startup Buzz Solutions out of Stanford, California just introduced its AI solution to help utilities quickly spot powerline and grid faults so repairs can be made before wildfires start. AI and machine vision technology, like that from Buzz Solutions, can take data from sources like ... [ ] this drone, helicopters, and aircraft to determine characteristics like powerline and grid faults so repairs can be made before wildfires start. Their unique platform uses AI and machine vision technology to analyze millions of images of powerlines and towers from drones, helicopters, and aircraft to find dangerous faults and flaws as well as overgrown vegetation, in and around the grid infrastructure to help utilities identify problem areas and repair them before a fire starts. This system can do the analysis at half the cost and in a fraction of the time compared to humans, hours to days not months to years. The California Department of Forestry and Fire Protection determined that PG&E's transmission lines were at fault for the huge Kincade Fire in Sonoma, California last year.
Based on the last two wildfire seasons, including 2018 when an entire California town was destroyed, utilities blamed for recent wildfires need all the help they can get maintaining aging grids. AI technologies may provide new monitoring tools. Paradise, Calif., population of about 27,000, was destroyed by the Camp Fire. The 2018 inferno claimed at least 84 victims. In June, Pacific Gas & Electric (PG&E) was ordered to pay a $3.5 million fine for causing the Camp Fire.
Azerbaijan and Armenia have accused each other of shelling military positions and villages, breaking a day of ceasefire in border clashes between the long-feuding former Soviet republics. The Azerbaijan defence ministry said on Thursday one of its soldiers died, while Armenia's defence ministry said a civilian was wounded in Chinari village from an Azeri drone attack. Prior to that, 15 soldiers from both sides and one civilian had died since Sunday in the flareup between nations who fought a 1990s war over the mountainous Nagorno-Karabakh region. In a blizzard of rhetoric on both sides, Azerbaijan warned Armenia it might attack the Metsamor nuclear power station if its Mingechavir reservoir or other strategic outlets were hit. The neighbours have long been in conflict over Azerbaijan's breakaway, mainly ethnic Armenian region of Nagorno-Karabakh. But the latest flareups are around the Tavush region in northeast Armenia, some 300km (190 miles) from the enclave.
Facebook Connectivity, in league with ULC Robotics, has developed a robot capable of winding optical fibre on live medium voltage (MV) power lines that typically serve residential areas in much of the world, at a claimed cost three to five times cheaper than traditional aerial fibre construction. Karthik Yogeeswaran, wireless systems engineer at Facebook Connectivity, said in a blog post the idea for the project came after travelling through rural Africa and noticing the ubiquity of power line infrastructure, which is far "more pervasive than the total fibre footprint of the country". In order to keep costs down, Facebook needed to lower the preparatory and manual work needed to wind fibre around power lines, and to minimise disruption of electrical services, the robot needed to able to do its job on a live line and be able to avoid and cross obstacles it encountered. Keeping the weight of the robot within the limits that a medium voltage power line could handle was a key challenge because it would limit the amount of fibre it could carry, so the size of the cable needed to be reduced. "Using the MV power line as a support adds a number of additional challenges. The first is the voltage stress. MV conductors can have a voltage as high as 35kV which can cause degradation phenomena such as tracking, partial discharge, and dry band arcing," Yogeeswaran said.
Facebook's experiments in internet connectivity haven't always gone well. But its latest innovation seems genuinely cool. Facebook Connectivity announced Monday that it has developed a robot that can travel along power lines deploying a thin yet durable fiber-optic cable of Facebook's own creation. It claims that this system, which utilizes the electrical grid to build out internet infrastructure, will be cheaper than the existing methods of laying internet cables, particularly in developing countries. That contributes to Facebook Connectivity's overall goal of increasing internet access.
Artificial Intelligence (AI) has arrived. It is not science fiction anymore. Computers already recognize objects in images and understand speech and language at least as well as, if not better than, humans. This has been made possible with rapid advances in hardware, vast amounts of training data, and innovations in machine learning algorithms such as deep neural networks. Deep learning is the driving force behind the current AI revolution and is giving intelligence to today's self-driving cars, smartphone and smart speakers, and making deep inroads into radiology and even gaming.
Digital Transformation is an ongoing process for utilities today. However, to be successful they must focus on technologies that deliver the services customers want. Machine Learning offers enormous potential for utilities to discover more about their customers and for solving the common issues utilities face every day. Today, it is undisputed that Digital Transformation is essential for utilities. However, organizations often find the results of their Digital Transformation efforts disappointing.