On Sunday, the city authorities named the affected districts as Podilskyi, Sviatoshynskyi and Shevchenkivskyi, all in or near the city centre. Kyiv's air defence system has proven effective at downing most Russian drones and missiles targeting the city.

Soil apparent electrical conductivity (ECa) is a vital metric in Precision Agriculture and Smart Farming, as it is used for optimal water content management, geological mapping, and yield prediction. Several existing methods seeking to estimate soil electrical conductivity are available, including physical soil sampling, ground sensor installation and monitoring, and the use of sensors that can obtain proximal ECa estimates. However, such methods can be either very laborious and/or too costly for practical use over larger field canopies. Robot-assisted ECa measurements, in contrast, may offer a scalable and cost-effective solution. In this work, we present one such solution that involves a ground mobile robot equipped with a customized and adjustable platform to hold an Electromagnetic Induction (EMI) sensor to perform semi-autonomous and on-demand ECa measurements under various field conditions. The platform is designed to be easily re-configurable in terms of sensor placement; results from testing for traversability and robot-to-sensor interference across multiple case studies help establish appropriate tradeoffs for sensor placement. Further, a developed simulation software package enables rapid and accessible estimation of terrain traversability in relation to desired EMI sensor placement. Extensive experimental evaluation across different fields demonstrates that the obtained robot-assisted ECa measurements are of high linearity compared with the ground truth (data collected manually by a handheld EMI sensor) by scoring more than 90% in Pearson correlation coefficient in both plot measurements and estimated soil apparent electrical conductivity maps generated by kriging interpolation. The proposed robotic solution supports autonomous behavior development in the field since it utilizes the Robot Operating System (ROS) navigation stack along with the Real-Time Kinematic (RTK) GNSS positioning data and features various ranging sensors. Agricultural geophysics employs non-invasive sensing techniques to characterize soil spatial variability and provide valuable insights into soil-plant-management relationships [1], [2]. Specifically, geospatial information on soil characteristics can indicate optimal cultivation approaches and may provide an estimate of expected yields [3], [4]. As such, it has been used widely across applications such as in agriculture, water management, geological mapping, and engineering surveys [5]-[7].

Drones are becoming versatile in a myriad of applications. This has led to the use of drones for spying and intruding into the restricted or private air spaces. Such foul use of drone technology is dangerous for the safety and security of many critical infrastructures. In addition, due to the varied low-cost design and agility of the drones, it is a challenging task to identify and track them using the conventional radar systems. In this paper, we propose a reinforcement learning based approach for identifying and tracking any intruder drone using a chaser drone. Our proposed solution uses computer vision techniques interleaved with the policy learning framework of reinforcement learning to learn a control policy for chasing the intruder drone. The whole system has been implemented using ROS and Gazebo along with the Ardupilot based flight controller. The results show that the reinforcement learning based policy converges to identify and track the intruder drone. Further, the learnt policy is robust with respect to the change in speed or orientation of the intruder drone.

Reducing unexpected urban traffic congestion caused by en-route events (e.g., road closures, car crashes, etc.) often requires fast and accurate reactions to choose the best-fit traffic signals. Traditional traffic light control systems, such as SCATS and SCOOT, are not efficient as their traffic data provided by induction loops has a low update frequency (i.e., longer than 1 minute). Moreover, the traffic light signal plans used by these systems are selected from a limited set of candidate plans pre-programmed prior to unexpected events' occurrence. Recent research demonstrates that camera-based traffic light systems controlled by deep reinforcement learning (DRL) algorithms are more effective in reducing traffic congestion, in which the cameras can provide high-frequency high-resolution traffic data. However, these systems are costly to deploy in big cities due to the excessive potential upgrades required to road infrastructure. In this paper, we argue that Unmanned Aerial Vehicles (UAVs) can play a crucial role in dealing with unexpected traffic congestion because UAVs with onboard cameras can be economically deployed when and where unexpected congestion occurs. Then, we propose a system called "AVARS" that explores the potential of using UAVs to reduce unexpected urban traffic congestion using DRL-based traffic light signal control. This approach is validated on a widely used open-source traffic simulator with practical UAV settings, including its traffic monitoring ranges and battery lifetime. Our simulation results show that AVARS can effectively recover the unexpected traffic congestion in Dublin, Ireland, back to its original un-congested level within the typical battery life duration of a UAV.

Deputy Secretary of Defense Kathleen Hicks addressed the plan and how the U.S. will continue to counter the rising aggression from China. The Pentagon has started to assess the possibility of developing an artificial intelligence (AI)-powered fleet of drones and autonomous systems that officials argue will allow the U.S. to compete with and counter threats from China. We are not seeking to be at war, but we have to be able to get this department to move with that same kind of urgency because the PRC isn't waiting," Kathleen Hicks, the deputy secretary of defense, said during an interview earlier this week with The Wall Street Journal. Hicks spoke about the potential uses of such an AI fleet during a speech on Wednesday, revealing the department would spend hundreds of millions of dollars on the project, aiming to produce thousands of systems for use over land, air and sea ready for first deployment within two years. China has focused heavily on AI research and development, producing ...

The beds are full at the National Centre for the Rehabilitation of Addicts (NCRA), one of only two public addiction rehabilitation facilities in Jordan. In the midst of the busy centre, Ahmad*, 34, takes a breath in the facility's garden. The young man is on his eighth day of treatment for addiction to crystal methamphetamine. Cases of crystal meth abuse are rising throughout Jordan – according to doctors and scientists, the drug is even more addictive and dangerous than the now widely-available and also highly-addictive amphetamine, captagon. "On crystal [meth], I felt I was a different person," he told Al Jazeera, glancing down at the tattoo sleeves that envelop his arms, his brothers' names inscribed around each bicep.

This article was copublished with The Markup, a nonprofit, investigative newsroom that challenges technology to serve the public good. Less than 10 days after the Robb Elementary School shooting in Uvalde, Texas, in May 2022, Axon Enterprises CEO Rick Smith announced the company had formally started developing Taser-equipped drones. The technology, Smith argued, could potentially save lives during mass shootings by incapacitating active shooters within seconds. For Axon, which changed its name from Taser in 2017, the concept seemed a sensible next step for stakeholders who share Axon's public safety mission, Smith said on the company's site. "In brief," he wrote, "non-lethal drones can be installed in schools and other venues and play the same role that sprinklers and other fire suppression tools do for firefighters: Preventing a catastrophic event, or at least mitigating its worst effects."

Excerpts from Walter Isaacson's Elon Musk biography are coming to light ahead of its release next week, revealing some new details about the billionaire's decision to provide Ukraine with Starlink access amid the country's war with Russia. According to an excerpt CNN reported on, Musk allegedly told SpaceX workers to shut down Starlink access close to the Crimea coast to prevent a Ukrainian drone attack on Russia's naval fleet. Musk, who has reportedly been in contact with Russian officials including President Vladimir Putin, is said to have been worried that the attack would lead to Russia retaliating with nuclear weapons. Ukrainian leaders seemingly begged Musk to reactivate Starlink access but drones that were approaching Russian warships "lost connectivity and washed ashore harmlessly," CNN cites Isaacson as stating. Musk's alleged actions have had significant consequences for Ukraine, according to Mykhailo Podolyak, an advisor to President Volodymyr Zelensky.

A senior Ukrainian official has accused Elon Musk of "committing evil" after a new biography revealed details about how the business magnate ordered his Starlink satellite communications network to be turned off near the Crimean coast last year to hobble a Ukrainian drone attack on Russian warships. In a statement on X, the social media platform formerly known as Twitter, which Musk owns, the Ukrainian presidential adviser Mykhailo Podolyak wrote that Musk's interference led to the deaths of civilians, calling them "the price of a cocktail of ignorance and big ego". "By not allowing Ukrainian drones to destroy part of the Russian fleet via Starlink interference, @elonmusk allowed this fleet to fire Kalibr missiles at Ukrainian cities. As a result, civilians, and children are being killed," Podolyak wrote. "Why do some people so desperately want to defend war criminals and their desire to commit murder? And do they now realise that they are committing evil and encouraging evil?" Sometimes a mistake is much more than just a mistake.

Russia's Federal Security Service (FSB) has detained a man for plotting a rail bombing in Crimea as a drone was downed over the Moscow-occupied peninsula. Crimea, which Russia seized from Ukraine in 2014, has been targeted by Ukrainian drone raids and sabotage attacks as Kyiv tries to retake the peninsula. The FSB said on Friday the suspect – a Russian citizen in his mid-40s – had been "collecting information on the deployment of Russian defence ministry facilities and units" and was preparing a railway bombing. "In a hiding place he had organised [we] found and seized an improvised explosive device made using foreign-made plastic explosives," it said. It said the man had been acting on the "instructions of Ukrainian military intelligence" and had been remanded in custody. Russia's TASS news agency said the man was a resident of the Crimean city of Sevastopol.