Latest news with #FCNs
Int'l Business Times
12-06-2025
- Science
- Int'l Business Times
Smarter Fields Ahead: How Deep Learning Is Shaping Sustainable Agriculture
In today's fast-paced technological landscape, innovation in agriculture has become more than a necessity—it's an imperative for survival. Tenny Enoch Devadas, a technology expert interested in sustainable systems, examines how deep learning transforms agriculture into a data-driven, efficient, and environmentally responsible domain. His work focuses on applying artificial intelligence to optimize farm operations and sustainability, offering compelling insights into how farmers can thrive amid climate unpredictability. Forecasting the Future: Weather-Driven Farming A key innovation in the research is using deep learning, including CNNs and LSTMs, to enhance weather forecasting. These models process spatial and temporal data, enabling accurate local predictions that help farmers optimize planting, irrigation, and harvesting, reducing uncertainty and the risk of crop failure. Digging Deep: Understanding Soil from the Sky Deep learning is revolutionizing soil analysis. With input from drone-captured multispectral images and soil sensors, algorithms can determine soil moisture, nutrient levels, and organic content. Techniques like semantic segmentation using Fully Convolutional Networks (FCNs) allow for real-time assessments, enabling farmers to manage soil health better. This targeted approach reduces unnecessary use of fertilizers and enhances overall soil longevity. Smarter Choices: Data-Guided Crop Selection Choosing the right crop once relied on intuition, but hybrid CNN-LSTM models now analyze soil, weather, market trends, and yield history to guide decisions. Continuously learning from new data, these models boost yield, cut input costs, and more effectively align farming with market demand. Mitigating Risk: From Pest Alerts to Market Trends Deep learning enhances productivity and resilience in agriculture. Convolutional Neural Networks (CNNs) detect pests and diseases early using satellite or ground-level images, preventing outbreaks. Long-short-term memory (LSTM) models analyze time-series data to forecast extreme weather. Additionally, AI models track global market trends to predict price shifts, helping farmers plan harvests and sales with greater financial foresight. This proactive risk management supports stable yields and incomes. Efficiency on the Ground: Resource Optimization Deep learning enables precision agriculture, allowing farmers to optimize input use. AI tailors irrigation schedules to crop needs and distributes fertilizer based on soil nutrition, reducing costs and conserving resources. Drone imagery identifies water-stressed zones, while targeted pesticide application addresses specific threats. These practices lower pollution and create more sustainable, efficient farms. Stronger Chains: Logistics and Distribution Reinvented Beyond the farm, deep learning transforms supply chains. Yield predictions guide inventory planning, transportation logistics, and labor allocation, minimizing waste. AI also supports inter-regional crop exchanges by analyzing demand, forecasting prices, and recommending transport strategies, boosting national food availability. Harmonizing Regions: Balancing Supply and Demand AI-driven models integrate local climate, soil, and demographic data to align agricultural production with regional needs. These tools produce crop suitability maps, enhance pricing models, and support adaptive logistics, fostering a stable, responsive food system. Green Thinking: Long-Term Sustainability Goals Sustainability is central to deep learning's agricultural applications. From optimizing crop rotation for soil regeneration to recommending pollinator-friendly planting schedules, these models encourage environmentally conscious farming. They even help evaluate ecosystem services like carbon sequestration and biodiversity preservation. These efforts collectively reduce agriculture's ecological footprint while improving productivity. Rooted in Science: Soil Health and Biodiversity Algorithms provide actionable insights into crop rotation schedules and soil amendment needs. They help prevent degradation by monitoring microbial activity, nutrient levels, and erosion risks. On the biodiversity front, models can map habitats, identify conservation priorities, and recommend strategies that support beneficial insects and wildlife—all without compromising yield. In conclusion, Tenny Enoch Devadas envisions a sustainable agricultural future empowered by deep learning. This technology tackles food security, resource scarcity, and environmental challenges through precision farming and smart logistics. Collaboration among experts and farmers is key to adapting solutions locally and building a resilient, data-driven agricultural system.
RTÉ News
27-05-2025
- RTÉ News
Limerick gardaí roll out new way to police e-scooters
In Limerick city, gardaí are rolling out a new way of policing electric scooters. Portable dynamometers come in two parts, look like a mini treadmill, and measure around 1.5 metres in length. They measure the speed of e-scooters - with 20km/h the maximum allowed. At a recent checkpoint on Bishop's Quay, a rider was flagged down by members of the Garda Roads Policing Unit, and her e-scooter was rolled up onto the new machine. Within a minute, it was deemed to be in compliance, and the woman is back on the road. However, a bigger model fails the test and is seized. "It goes up to 47km/h," said Garda Philip Ellard, who is conducting the test. "It's very fast. If you had an accident on this, you'd have serious injuries. It's like being on the equivalent of a small moped. "The limit is 20 km/h, anything that exceeds that can't be used on any roads for any reason," he said. Watch: Limerick gardaí roll out new way to police e-scooters Inspector Padraig Sutton is in charge of the checkpoint. "There's lots of e-scooters around Limerick city. Once they conform to the rules, they're a very useful tool for moving around. However, there are quite a number of people who use illegal ones," he said. "Unfortunately in this jurisdiction, we've had serious injury collisions and also fatalities as a result of e-scooter use," he said. There are now four dynamometers used by the Garda Roads Policing Unit across the country and they have been in use for the last two months. "It's been an excellent device for us, because prior to now, it's very difficult for us to estimate with any accuracy the speed of in of an e-bike or an e-scooter, other than actually using a laser speed device." "So, it's a very useful and portable machine that we're getting good use of here in the Limerick division", he said. "Officers can seize an e-scooter and they can bring it back to the station where we can test it, or we can take it out to different parts of the county and set it up and have a mobile checkpoint and target those who are using our roads illegally with devices that really shouldn't be on roads," Inspector Sutton said. The number of e-scooters seized by gardaí has increased dramatically since the introduction of new regulations around their use. The number jumped from 26 to 130 for the five months of this year compared to last. The data also shows that there have been 406 fines given to riders since the new rules were introduced. The laws mean that using an e-scooter to carry goods or passengers, driving on a footpath, or when on a mobile phone all now attract garda Fixed Charge Notices (FCNs) of €50. Other infringements are also included. The challenge for gardaí will be trying to keep up with the number of e-scooters on the roads. Research from the Road Safety Authority suggests that their number will double in the next year. Currently, it is estimated around 4% of adults own one. "It can be a very good way of travelling, particularly around cities. However, we're also seeing a lot of incidents, crashes and collisions," said David Martin from the RSA. "They're growing in popularity. But clearly, there's an issue in terms of safety, and it's something that we are concerned about," he said, adding that the research the RSA commissioned indicates that one in four have had a crash in the last 12 months, and one in three have had a near miss. The RSA, he said, welcomes the roll out of the new dynamometers. "We welcome this initiative today and think it's a tremendous development. "The speed limit of 20 km/h - very difficult for the gardaí to have checked that in the past. So, this new development really is welcome," he said.
Irish Times
24-04-2025
- Irish Times
Challenge issued over alleged speeding in average speed zone rejected by High Court
A test challenge to the legal adequacy of a fixed-charge notice (FCN) issued over alleged speeding in an average speed zone has been rejected by the High Court . The decision has adverse implications for more than 2,000 drivers who were allegedly caught speeding in an average speed zone on the M7 motorway. Ms Justice Miriam O'Regan, in a judgment on Wednesday, determined the key legal issues in Edel O'Brien's test case in favour of the Director of Public Prosecutions , represented by barrister David Staunton. The case concerned a FCN issued to Ms O'Brien, of Springhill Avenue, Deansgrange, Co Dublin, who is alleged to have driven at 131km/h on the M7 at Birdhill (west), where a 120km/h limit applies, on September 7th, 2022. READ MORE A core issue was whether the absence of the word 'average' from FCNs, when issued for alleged speeding in an average speed zone, makes them so defective that a conviction cannot be registered on foot of them. About 900 other cases stand adjourned, and 1,500 summonses for alleged speeding in an average speed zone have yet to issue, pending the outcome of the High Court decision on legal issues referred by District Court Judge Miriam Walsh arising from Ms O'Brien's case. Average speed cameras record vehicles at two distinct points a set distance apart, allowing for its speed to be calculated over a longer distance than a single static camera. The system was first introduced in Ireland in 2017 at the Dublin Port Tunnel. It was introduced on the M7 between junction 26 Nenagh and junction 27 Birdhill in April 2022. It sits alongside the statutory regime for prosecuting speeding offences under the Road Traffic Acts. A driver must be served with a FCN alleging the commission of a speeding offence on a particular date and at particular location, irrespective of how the speed has been detected, before a prosecution can be taken. After Ms O'Brien was served with her FCN, she contacted the Garda processing office querying the content of the FCN and said she was told, for the first time, the allegation related to a recorded average speed over a 9km distance. When she did not pay the notice, she was summonsed to appear before Nenagh District Court in March of last year. In sending legal issues to be determined by the High Court, Judge Walsh said Ms O'Brien, representing herself, had pleaded guilty and accepted she had been speeding in excess of the 120km/h limit, but she raised an issue about FCN not referring to the word 'average' with reference to the 131km/h speed alleged. Ms O'Brien argued the FCN materially misstated the particulars of the allegation, which was that her car was driven at an average speed of 131km/h over a distance of 9km, in excess of the permitted limit. The FCN, she claimed, contained misstatements likely to prejudice her in deciding whether to pay or contest the matter. She would have paid the notice had it accurately set out her alleged speeding offence, she contended. In her judgment, Ms Justice O'Regan found the FCN had been duly served and the error in the form of it did not render it invalid unless Ms O'Brien was misled by it. Given the lack of evidence to that effect, the judge found the FCN complied with the regulations and statutory provisions. She further held any perceived error could be dealt with under the Interpretation Act. The fact Ms O'Brien later became aware it was an average speed of 131km/h at a time she could still accept and pay the FCN was relevant to whether or not she had been afforded adequate information on the allegation against her and in dealing with any prejudice asserted, the judge held. The variation between the complaint and the evidence adduced in support of it therefore did not affect the court's entitlement to record a conviction, she ruled.
