Urban Data Talks #2 presentation, focused on how urban data such as footfall tells us about changing human behaviour pre-pandemic and for the economic recovery post pandemic.
Talk by Sophie Meszaros from Open and Agile Smart Cities at Urban Data Talks #6 event on progress of european work on data spaces for sustainable smart cities and communities.
Inisghts from data to plan and optimise shared bike usageAlex Gluhak
油
Talk by Merja Kajava at Urban Data Talks #6 event, focused on how she uses urban data obtained from bike sharing docks and systems to better understand shared bike usage and improve the management of such systems
Talk by Roy Lin from Tapei Urban Intelligence Centre @Urban Data Talks#6 event. Background about the centre and use cases of how Taipei uses urban data and analytics to solve urban challenges the city faces.
Cities In Charge: How urban data can improve the operation of Public EV charg...Alex Gluhak
油
CitiesInCharge is a data-driven decision support tool created by Urban Data Collective to help electric vehicle (EV) infrastructure owners and providers optimize the rollout, management, and utilization of public EV charging points. It uses data from various sources like parking occupancy and the Urban Data Exchange to provide insights into network and infrastructure planning, operational health, utilization hotspots, blocked charger violations, energy usage and emissions, revenue opportunities, and sustainable energy tariff strategies. The tool is designed to help infrastructure owners and providers maximize utilization of public charging assets and support the transition to more electric vehicles.
Talk by Kris Vanherle sharing his story of building Telraam, a large crowd-sourced platform of traffic counting devices that empowers a growing international community of citizens to influence local mobility policy.
Leveraging the Platform effect for citiesAlex Gluhak
油
Urban Data Talks #4 presentation by Alanus von Radecki, Deutsches Kompetenz Zentrum fuer Staedte und Region, outlining how effective collaboration with various cities and municipal companies can support the scaling of smart city use cases.
Urban Data Talks #4 Presentation - Presentation by Jaime Ventura (Porto Digital) providing insights into the creation of Porto's open data platform, its internal workings and use cases realised on top of it.
The document discusses establishing a High Streets Data Service partnership between the GLA and London boroughs to collect and share data about London's high streets. Key goals are cost savings through shared data collection/purchasing, collaboration to build a comprehensive London-wide picture, and capacity building by sharing skills and knowledge. The service would collect footfall, spending, vacancy and other data to provide insights about recovery from the pandemic across different high street types and neighborhoods. Analysis could help inform planning and community safety work. 24 of 33 boroughs have committed to joining the partnership.
Urban observatory talk by Phil James, Newcastle UniversityAlex Gluhak
油
Talk at Urban Data Talks Meetup event #3. Presents the urban obervatory in nNewcastle and how it allows agile policy making based on data from IoT deployments and existing urban infrastructure.
Smart Citizen - Sense Making - scar Gonz叩lez, Fablab Barcelona Alex Gluhak
油
Talk at Urban Data Talks event #3. Fab Labs Barcelona's journey from Smart Cities to Smart Citizens. Tools and methodologies to empower smarter citizens
Local government levelled up - IoT innovation in NorfolkAlex Gluhak
油
This talk presented at Urban Data Talks#2 by Kurt Frary from Norfolk City Council provides an overview of a large number of IoT use cases carried out during the pandemic around an open LoRaWAN innovation network.
Nature smart Cities - New technologies for assessing Biodiversity in Cities ...Alex Gluhak
油
This talk at the Urban Data Talks#2 by Allison Fairbrass (UCL), explores technology advances in biodiversity monitoring of cities, using IoT sensors and AI technologies.
This talk by Rory Maxwell from Ethos explores how urban data can provide more confidence to disabled public transport users and help the live more independent lives to avoid social isolation.
The document discusses the growing consumer internet of things (IoT) market, which is projected to grow from 40 billion installed devices in 2018 to over 1 billion devices by 2025. It notes that startups and telecommunications companies are competing to establish ecosystems in the consumer IoT space in Asia and other markets. The document advocates that the company build its own ecosystem to shape its destiny and acquire skills to engage customers where they are, like individual use cases, price, experience and addressing customer inertia.
CityGate - IoT platform and smart lorawan applications in BirminghamAlex Gluhak
油
The document summarizes the CityGate IoT urban data platform project at Birmingham City University. CityGate aims to collect, integrate, and analyze big data from IoT sensors in cities to improve urban systems and quality of life. It discusses BCU's smart city infrastructure and IoT community network, the CityGate platform capabilities and modules, and example use cases like air quality monitoring, people counting, and traffic sensing. CityGate utilizes open-source technologies like LoRaWAN, APIs, databases, and analytics to enable applications and extract value from urban IoT data.
Assistive living applications for elderly care based on Sigfox technology,Alex Gluhak
油
This document discusses the development of technology-enabled care from 2012-2019, starting with early prototypes using WiFi and Bluetooth before moving to production models using GSM cellular networks. It outlines how sensors can monitor things like temperature, falls, fires, location and water leaks to benefit those over 85 years old, who are the fastest growing demographic and most likely to develop dementia. The goal is to enable longer independent living with fewer carers through low-cost national networks connecting IoT sensors to common web platforms and 24/7 emergency response.
This document summarizes an experimental study on the impact of temperature variations on the reliability of LoRa networks. The study found that increasing temperatures can compromise LoRa links by increasing packet corruption and loss. The impact varies based on the radio hardware used. Mitigation techniques include selecting more robust physical layer settings like lower bandwidth or higher spreading factor. Nodes should autonomously adapt settings based on monitored on-board temperature to maintain performance in varying conditions. Careful deployment and shielding of orchestrator nodes from sunlight is also important for reliability.
Emma Cronin is the Strategic Channel Partner Manager at Wireless Network Developments (UK) Ltd, the UK operator of the Sigfox low power wide area network. The document discusses WNDUK's progress in building out the Sigfox network in the UK, including personnel changes and expanding their team. It outlines their channel partner model and examples of pilot projects and potential customers in various verticals like logistics, manufacturing, utilities and more.
Introduction to Generative Artificial IntelligenceLoic Merckel
油
The buzz around Generative AI (GenAI) is louder than everbut are we seeing the whole picture?
This presentation was designed for a broad audience, avoiding technical jargon while addressing the real opportunities and challenges AI brings.
A few key insights from the presentation:
Innovation under constraint: DeepSeek achieved remarkable results at a fraction of competitors' costs.
The productivity paradox: AI may boost output for writers and coders but may reduce job satisfaction for scientists.
The shifting definition: "AI is what computers can't do; once they can, it's just software." Mustafa Suleyman
The GPU Bottleneck: Big Tech is turning to custom chips and nuclear energy to meet AI's soaring computational demands.
誌 Energy-Hungry AI: AI's energy needs are driving investments in dedicated nuclear power for datacenters.
際際滷 decks are meant to support live talks, so they might not capture the full story on their own. If you are curious to dive deeper, feel free to reach outI would be happy to discuss these ideas in a more interactive setting.
Feel free to check out the slides here and my LinkedIn post for further discussion: https://www.linkedin.com/posts/merckel_intro-to-genai-activity-7300095492862930946-rnL9
BEST MACHINE LEARNING INSTITUTE IS DICSITCOURSESgs5545791
油
Machine learning is revolutionizing the way technology interacts with data, enabling systems to learn, adapt, and make intelligent decisions without human intervention. It plays a crucial role in various industries, from healthcare and finance to automation and artificial intelligence. If you want to build a successful career in this field, joining the Best Machine Learning Institute In Rohini is the perfect step. With expert-led training, hands-on projects, and industry-recognized certifications, youll gain the skills needed to thrive in the AI-driven world. If you are interested, then Enroll Fast limited seats are available!
Large Language Models (LLMs) part one.pptxharmardir
油
**The Rise and Impact of Large Language Models (LLMs)**
**Introduction**
In the rapidly evolving landscape of artificial intelligence (AI), one of the most groundbreaking advancements has been the development of Large Language Models (LLMs). These AI systems, trained on massive amounts of text data, have demonstrated remarkable capabilities in understanding, generating, and manipulating human language. LLMs have transformed industries, reshaped the way people interact with technology, and raised ethical concerns regarding their usage. This essay delves into the history, development, applications, challenges, and future of LLMs, providing a comprehensive understanding of their significance.
**Historical Background and Development**
The foundation of LLMs is built on decades of research in natural language processing (NLP) and machine learning (ML). Early language models were relatively simple and rule-based, relying on statistical methods to predict word sequences. However, the emergence of deep learning, particularly the introduction of neural networks, revolutionized NLP. The introduction of recurrent neural networks (RNNs) and long short-term memory (LSTM) networks in the late 1990s and early 2000s allowed for better sequential data processing.
The breakthrough moment for LLMs came with the development of Transformer architectures, introduced in the seminal 2017 paper "Attention Is All You Need" by Vaswani et al. The Transformer model enabled more efficient parallel processing and improved context understanding. This led to the creation of models like BERT (Bidirectional Encoder Representations from Transformers) and OpenAIs GPT (Generative Pre-trained Transformer) series, which have since set new benchmarks in AI-driven text generation and comprehension.
**Core Mechanisms of LLMs**
LLMs rely on deep neural networks trained on extensive datasets comprising books, articles, websites, and other textual resources. The training process involves:
1. **Tokenization:** Breaking down text into smaller units (words, subwords, or characters) to be processed by the model.
2. **Pretraining:** The model learns general language patterns through unsupervised learning, predicting missing words or the next sequence in a text.
3. **Fine-tuning:** Adjusting the model for specific tasks, such as summarization, translation, or question-answering, using supervised learning.
4. **Inference:** The trained model generates text based on user input, leveraging probabilistic predictions to produce coherent responses.
Through these mechanisms, LLMs can perform a wide range of linguistic tasks with human-like proficiency.
**Applications of LLMs**
LLMs have found applications across various domains, including but not limited to:
1. **Content Generation:** LLMs assist in writing articles, blogs, poetry, and even code, helping content creators enhance productivity.
2. **Customer Support:** Chatbots and virtual assistants powered by LLMs provide automated yet cont
The document discusses establishing a High Streets Data Service partnership between the GLA and London boroughs to collect and share data about London's high streets. Key goals are cost savings through shared data collection/purchasing, collaboration to build a comprehensive London-wide picture, and capacity building by sharing skills and knowledge. The service would collect footfall, spending, vacancy and other data to provide insights about recovery from the pandemic across different high street types and neighborhoods. Analysis could help inform planning and community safety work. 24 of 33 boroughs have committed to joining the partnership.
Urban observatory talk by Phil James, Newcastle UniversityAlex Gluhak
油
Talk at Urban Data Talks Meetup event #3. Presents the urban obervatory in nNewcastle and how it allows agile policy making based on data from IoT deployments and existing urban infrastructure.
Smart Citizen - Sense Making - scar Gonz叩lez, Fablab Barcelona Alex Gluhak
油
Talk at Urban Data Talks event #3. Fab Labs Barcelona's journey from Smart Cities to Smart Citizens. Tools and methodologies to empower smarter citizens
Local government levelled up - IoT innovation in NorfolkAlex Gluhak
油
This talk presented at Urban Data Talks#2 by Kurt Frary from Norfolk City Council provides an overview of a large number of IoT use cases carried out during the pandemic around an open LoRaWAN innovation network.
Nature smart Cities - New technologies for assessing Biodiversity in Cities ...Alex Gluhak
油
This talk at the Urban Data Talks#2 by Allison Fairbrass (UCL), explores technology advances in biodiversity monitoring of cities, using IoT sensors and AI technologies.
This talk by Rory Maxwell from Ethos explores how urban data can provide more confidence to disabled public transport users and help the live more independent lives to avoid social isolation.
The document discusses the growing consumer internet of things (IoT) market, which is projected to grow from 40 billion installed devices in 2018 to over 1 billion devices by 2025. It notes that startups and telecommunications companies are competing to establish ecosystems in the consumer IoT space in Asia and other markets. The document advocates that the company build its own ecosystem to shape its destiny and acquire skills to engage customers where they are, like individual use cases, price, experience and addressing customer inertia.
CityGate - IoT platform and smart lorawan applications in BirminghamAlex Gluhak
油
The document summarizes the CityGate IoT urban data platform project at Birmingham City University. CityGate aims to collect, integrate, and analyze big data from IoT sensors in cities to improve urban systems and quality of life. It discusses BCU's smart city infrastructure and IoT community network, the CityGate platform capabilities and modules, and example use cases like air quality monitoring, people counting, and traffic sensing. CityGate utilizes open-source technologies like LoRaWAN, APIs, databases, and analytics to enable applications and extract value from urban IoT data.
Assistive living applications for elderly care based on Sigfox technology,Alex Gluhak
油
This document discusses the development of technology-enabled care from 2012-2019, starting with early prototypes using WiFi and Bluetooth before moving to production models using GSM cellular networks. It outlines how sensors can monitor things like temperature, falls, fires, location and water leaks to benefit those over 85 years old, who are the fastest growing demographic and most likely to develop dementia. The goal is to enable longer independent living with fewer carers through low-cost national networks connecting IoT sensors to common web platforms and 24/7 emergency response.
This document summarizes an experimental study on the impact of temperature variations on the reliability of LoRa networks. The study found that increasing temperatures can compromise LoRa links by increasing packet corruption and loss. The impact varies based on the radio hardware used. Mitigation techniques include selecting more robust physical layer settings like lower bandwidth or higher spreading factor. Nodes should autonomously adapt settings based on monitored on-board temperature to maintain performance in varying conditions. Careful deployment and shielding of orchestrator nodes from sunlight is also important for reliability.
Emma Cronin is the Strategic Channel Partner Manager at Wireless Network Developments (UK) Ltd, the UK operator of the Sigfox low power wide area network. The document discusses WNDUK's progress in building out the Sigfox network in the UK, including personnel changes and expanding their team. It outlines their channel partner model and examples of pilot projects and potential customers in various verticals like logistics, manufacturing, utilities and more.
Introduction to Generative Artificial IntelligenceLoic Merckel
油
The buzz around Generative AI (GenAI) is louder than everbut are we seeing the whole picture?
This presentation was designed for a broad audience, avoiding technical jargon while addressing the real opportunities and challenges AI brings.
A few key insights from the presentation:
Innovation under constraint: DeepSeek achieved remarkable results at a fraction of competitors' costs.
The productivity paradox: AI may boost output for writers and coders but may reduce job satisfaction for scientists.
The shifting definition: "AI is what computers can't do; once they can, it's just software." Mustafa Suleyman
The GPU Bottleneck: Big Tech is turning to custom chips and nuclear energy to meet AI's soaring computational demands.
誌 Energy-Hungry AI: AI's energy needs are driving investments in dedicated nuclear power for datacenters.
際際滷 decks are meant to support live talks, so they might not capture the full story on their own. If you are curious to dive deeper, feel free to reach outI would be happy to discuss these ideas in a more interactive setting.
Feel free to check out the slides here and my LinkedIn post for further discussion: https://www.linkedin.com/posts/merckel_intro-to-genai-activity-7300095492862930946-rnL9
BEST MACHINE LEARNING INSTITUTE IS DICSITCOURSESgs5545791
油
Machine learning is revolutionizing the way technology interacts with data, enabling systems to learn, adapt, and make intelligent decisions without human intervention. It plays a crucial role in various industries, from healthcare and finance to automation and artificial intelligence. If you want to build a successful career in this field, joining the Best Machine Learning Institute In Rohini is the perfect step. With expert-led training, hands-on projects, and industry-recognized certifications, youll gain the skills needed to thrive in the AI-driven world. If you are interested, then Enroll Fast limited seats are available!
Large Language Models (LLMs) part one.pptxharmardir
油
**The Rise and Impact of Large Language Models (LLMs)**
**Introduction**
In the rapidly evolving landscape of artificial intelligence (AI), one of the most groundbreaking advancements has been the development of Large Language Models (LLMs). These AI systems, trained on massive amounts of text data, have demonstrated remarkable capabilities in understanding, generating, and manipulating human language. LLMs have transformed industries, reshaped the way people interact with technology, and raised ethical concerns regarding their usage. This essay delves into the history, development, applications, challenges, and future of LLMs, providing a comprehensive understanding of their significance.
**Historical Background and Development**
The foundation of LLMs is built on decades of research in natural language processing (NLP) and machine learning (ML). Early language models were relatively simple and rule-based, relying on statistical methods to predict word sequences. However, the emergence of deep learning, particularly the introduction of neural networks, revolutionized NLP. The introduction of recurrent neural networks (RNNs) and long short-term memory (LSTM) networks in the late 1990s and early 2000s allowed for better sequential data processing.
The breakthrough moment for LLMs came with the development of Transformer architectures, introduced in the seminal 2017 paper "Attention Is All You Need" by Vaswani et al. The Transformer model enabled more efficient parallel processing and improved context understanding. This led to the creation of models like BERT (Bidirectional Encoder Representations from Transformers) and OpenAIs GPT (Generative Pre-trained Transformer) series, which have since set new benchmarks in AI-driven text generation and comprehension.
**Core Mechanisms of LLMs**
LLMs rely on deep neural networks trained on extensive datasets comprising books, articles, websites, and other textual resources. The training process involves:
1. **Tokenization:** Breaking down text into smaller units (words, subwords, or characters) to be processed by the model.
2. **Pretraining:** The model learns general language patterns through unsupervised learning, predicting missing words or the next sequence in a text.
3. **Fine-tuning:** Adjusting the model for specific tasks, such as summarization, translation, or question-answering, using supervised learning.
4. **Inference:** The trained model generates text based on user input, leveraging probabilistic predictions to produce coherent responses.
Through these mechanisms, LLMs can perform a wide range of linguistic tasks with human-like proficiency.
**Applications of LLMs**
LLMs have found applications across various domains, including but not limited to:
1. **Content Generation:** LLMs assist in writing articles, blogs, poetry, and even code, helping content creators enhance productivity.
2. **Customer Support:** Chatbots and virtual assistants powered by LLMs provide automated yet cont
How the Best News APIs Work: A Visual GuideContify
油
Discover how the best news APIs function with this visual guide. Learn how they fetch real-time news, filter content, and integrate seamlessly with apps. Understand key features like authentication, endpoints, and data formats, making it easier to choose the right API for your needs. Perfect for developers and businesses!
For more information please visit here https://www.contify.com/news-api/
Analyzing Consumer Spending Trends and Purchasing Behavioromololaokeowo1
油
This project explores consumer spending patterns using Kaggle-sourced data to uncover key trends in purchasing behavior. The analysis involved cleaning and preparing the data, performing exploratory data analysis (EDA), and visualizing insights using ExcelI. Key focus areas included customer demographics, product performance, seasonal trends, and pricing strategies. The project provided actionable insights into consumer preferences, helping businesses optimize sales strategies and improve decision-making.
International Journal on Cloud Computing: Services and Architecture (IJCCSA)ijccsa
油
Cloud computing helps enterprises transform business and technology. Companies have begun to
look for solutions that would help reduce their infrastructure costs and improve profitability. Cloud
computing is becoming a foundation for benefits well beyond IT cost savings. Yet, many business
leaders are concerned about cloud security, privacy, availability, and data protection. To discuss
and address these issues, we invite researches who focus on cloud computing to shed more light
on this emerging field. This peer-reviewed open access Journal aims to bring together researchers
and practitioners in all security aspects of cloud-centric and outsourced computing, including (but
not limited to):
The #IncomeTaxBill 2025 simplifies capital gains taxation by removing exemptions, restricting tax benefits to long-term gains, and limiting indexation. Here is our detailed analysis of the proposed changes.
HIRE MUYERN TRUST HACKER FOR AUTHENTIC CYBER SERVICESanastasiapenova16
油
Its hard to imagine the frustration and helplessness a 65-year-old man with limited computer skills must feel when facing the aftermath of a crypto scam. Recovering a hacked trading wallet can feel like an absolute nightmare, especially when every step seems to lead you into an endless loop of failed solutions. Thats exactly what I went through over the past four weeks. After my trading wallet was compromised, the hacker changed my email address, password, and even removed my phone number from the account. For someone with little technical expertise, this was not just overwhelming, it was a disaster. Every suggested solution I came across in online help centers was either too complex or simply ineffective. I tried countless links, tutorials, and forums, only to find myself stuck, not even close to reclaiming my stolen crypto. In a last-ditch effort, I turned to Google and stumbled upon a review about MUYERN TRUST HACKER. At first, I was skeptical, like anyone would be in my position. But the glowing reviews, especially from people with similar experiences, gave me a glimmer of hope. Despite my doubts, I decided to reach out to them for assistance.The team at MUYERN TRUST HACKER immediately put me at ease. They were professional, understanding, and reassuring. Unlike other services that felt impersonal or automated, they took the time to walk me through every step of the recovery process. The fact that they were willing to schedule a 25-minute session to help me properly secure my account after recovery was invaluable. Today, Im grateful to say that my stolen crypto has been fully recovered, and my account is secure again. This experience has taught me that sometimes, even when you feel like all hope is lost, theres always a way to fight back. If youre going through something similar, dont give up. Reach out to MUYERN TRUST HACKER. Even if youve already tried everything, their expertise and persistence might just be the solution you need.I wholeheartedly recommend MUYERN TRUST HACKER to anyone facing the same situation. Whether youre a novice or experienced in technology, theyre the right team to trust when it comes to recovering stolen crypto or securing your accounts. Dont hesitate to contact them, it's worth it. Reach out to them on telegram at muyerntrusthackertech or web: ht tps :// muyerntrusthacker . o r g for faster response.
Design Data Model Objects for Analytics, Activation, and AIaaronmwinters
油
Explore using industry-specific data standards to design data model objects in Data Cloud that can consolidate fragmented and multi-format data sources into a single view of the customer.
Design of the data model objects is a critical first step in setting up Data Cloud and will impact aspects of the implementation, including the data harmonization and mappings, as well as downstream automations and AI processing. This session will provide concrete examples of data standards in the education space and how to design a Data Cloud data model that will hold up over the long-term as new source systems and activation targets are added to the landscape. This will help architects and business analysts accelerate adoption of Data Cloud.
Optimizing Common Table Expressions in Apache Hive with CalciteStamatis Zampetakis
油
In many real-world queries, certain expressions may appear multiple times, requiring repeated computations to construct the final result. These recurring computations, known as common table expressions (CTEs), can be explicitly defined in SQL queries using the WITH clause or implicitly derived through transformation rules. Identifying and leveraging CTEs is essential for reducing the cost of executing complex queries and is a critical component of modern data management systems.
Apache Hive, a SQL-based data management system, provides powerful mechanisms to detect and exploit CTEs through heuristic and cost-based optimization techniques.
This talk delves into the internals of Hive's planner, focusing on its integration with Apache Calcite for CTE optimization. We will begin with a high-level overview of Hive's planner architecture and its reliance on Calcite in various planning phases. The discussion will then shift to the CTE rewriting phase, highlighting key Calcite concepts and demonstrating how they are employed to optimize CTEs effectively.
9. svenlatham.com @svenlatham
A leap forward in "progress" post-Covid:
Increased proportion of online shopping.
More visits attributed to leisure.
WFH shifting lunch & after-work trade.
More specialised/targeted retail trips.
10. svenlatham.com @svenlatham
Footfall is not just cameras
"People
Counts"
Time of Day
Noggin Footfall Camera (top) vs Phone Sensor (bottom) comparison: Christmas Lights Switch-on, 2016.
Dashed line was previous week. Event is highlighted.