The document proposes a mobility city project with the goal of improving mobility in cities. It involves creating a sensor network to develop several applications, including an intelligent parking management system, public transportation optimization system, and intelligent traffic management system. The parking system would use sensors to monitor spaces and provide real-time parking availability to drivers. The transportation system would provide real-time transit information to citizens. A prototype would be built in a high-traffic area of Madrid to demonstrate the solution. The goal is to eventually implement the system across Spanish cities and globally to help address mobility issues in urban areas.
The document proposes creating an interconnected smart city network using sensors to improve quality of life for citizens. It focuses on developing an intelligent parking management system using sensors to monitor parking spaces and guide citizens to available spots via their smartphones. While initial cost analyses estimated recouping investments within 7 years by charging users €11 annually for an app, customer feedback revealed most people only want to pay €0-2 or have the app be free, disrupting the business model. As an alternative, the document suggests licensing the technology to GPS/smartphone companies to integrate it rather than directly selling the app to users.
Cloud Based Autonomous Vehicle NavigationWilliam Smith
This document proposes a cloud-based autonomous vehicle control and navigation system that allows vehicles to cooperatively sense obstacles and avoid traffic. It involves the following:
1. RC cars equipped with sensors and microprocessors that can detect obstacles and communicate with a remote server via cloud.
2. A remote server runs an algorithm to determine the optimal path for each vehicle based on its location and destination, using real-time sensor data from vehicles about obstacles.
3. The system aims to scale to large numbers of autonomous vehicles by distributing sensing and control - vehicles only need to sense their environment and follow path instructions from the remote server.
Innovative system for autonomous charging of Road toll and parking fee.Abraham Paul
This document proposes an innovative system for uniformly charging road tolls and parking fees using wireless technology and GPS networks. The system would replace physical toll booths and parking tickets. A tamper-proof device in each vehicle would use GPS to track location and charge usage-based fees. Fees could vary by location, time of day, and vehicle type. The system aims to streamline fee collection while preventing non-compliance through continuous monitoring. It could generate substantial revenue from road/parking fees as well as value-added services.
The Parking Availability Network is a proposed system that uses sensors embedded in parking spaces and vehicles to track parking availability across a city. Static sensors mark spaces and provide information like occupancy. Mobile sensors in vehicles scan static sensors to tag spaces as occupied or not. This creates a map of parking availability that is integrated with vehicle navigation to help drivers find spaces and reduce congestion. The system also enables dynamic pricing to encourage use of less popular spaces.
This document proposes a novel three-tier vehicle cloud architecture to provide real-time services for cloud computing enabled vehicle networks. The three tiers include the device level, communication level, and service level. The device level includes sensors that can form an in-vehicle body area sensor network. The communication level allows vehicle-to-vehicle and vehicle-to-infrastructure communication. The service level provides context-based, communication-based, and customized services using cloud computing, such as real-time road traffic monitoring and driver healthcare monitoring. The architecture aims to improve safety, convenience, and comfort for drivers.
Traffic Congestion Prediction using Deep Reinforcement Learning in Vehicular ...IJCNCJournal
In recent years, a new wireless network called vehicular ad-hoc network (VANET), has become a popular research topic. VANET allows communication among vehicles and with roadside units by providing information to each other, such as vehicle velocity, location and direction. In general, when many vehicles likely to use the common route to proceed to the same destination, it can lead to a congested route that should be avoided. It may be better if vehicles are able to predict accurately the traffic congestion and then avoid it. Therefore, in this work, the deep reinforcement learning in VANET to enhance the ability to predict traffic congestion on the roads is proposed. Furthermore, different types of neural networks namely Convolutional Neural Network (CNN), Multilayer Perceptron (MLP) and Long Short-Term Memory (LSTM) are investigated and compared in this deep reinforcement learning model to discover the most effective one. Our proposed method is tested by simulation. The traffic scenarios are created using traffic simulator called Simulation of Urban Mobility (SUMO) before integrating with deep reinforcement learning model. The simulation procedures, as well as the programming used, are described in detail. The performance of our proposed method is evaluated using two metrics; the average travelling time delay and average waiting time delay of vehicles. According to the simulation results, the average travelling time delay and average waiting time delay are gradually improved over the multiple runs, since our proposed method receives feedback from the environment. In addition, the results without and with three different deep learning algorithms, i.e., CNN, MLP and LSTM are compared. It is obvious that the deep reinforcement learning model works effectively when traffic density is neither too high nor too low. In addition, it can be concluded that the effective algorithms for traffic congestion prediction models in descending order are MLP, CNN, and LSTM, respectively.
Online/Offline Lane Change Events Detection AlgorithmsFeras Tanan
Abstract—in this paper, We are presenting two algorithms
for lane change detection. The first one is used
for online detection (real-time detection) with accuracy of
85% and the other one is used for offline detection with
accuracy of 95%. The main purpose of the offline detection
algorithm is to find at which GPS locations the number
of happened left/right lane changes.
For the purpose of these algorithms we used the
”crowd-sensing” approach which means that the sensors of
different mobile devices that were fixed in different cars
are the sources of input data for the above mentioned
algorithms. Specifically speaking, we used Accelerometer
and Gyroscope sensors. We also presented an algorithm
for blinker pattern extraction using the microphone sensor.
Keywords: Pattern Extraction, Lane Change detection,
Accelerometer, Gyroscope and Crowd Sensing
The document summarizes an innovation workshop held by ADM. It discusses establishing an innovation ecosystem and funnel management. Key points include:
- Jan Dilis presented on the innovation funnel and how it can stifle innovation by allowing little room for failure.
- The group will work collaboratively until April 18th to develop a case study on an innovation ecosystem for ADM aligned with its business goals.
- Tasks are assigned with deadlines to define the ecosystem, analyze ADM's innovation needs, and propose changes to create an innovative culture.
The document proposes creating an interconnected smart city network using sensors to improve quality of life for citizens. It focuses on developing an intelligent parking management system using sensors to monitor parking spaces and guide citizens to available spots via their smartphones. While initial cost analyses estimated recouping investments within 7 years by charging users €11 annually for an app, customer feedback revealed most people only want to pay €0-2 or have the app be free, disrupting the business model. As an alternative, the document suggests licensing the technology to GPS/smartphone companies to integrate it rather than directly selling the app to users.
Cloud Based Autonomous Vehicle NavigationWilliam Smith
This document proposes a cloud-based autonomous vehicle control and navigation system that allows vehicles to cooperatively sense obstacles and avoid traffic. It involves the following:
1. RC cars equipped with sensors and microprocessors that can detect obstacles and communicate with a remote server via cloud.
2. A remote server runs an algorithm to determine the optimal path for each vehicle based on its location and destination, using real-time sensor data from vehicles about obstacles.
3. The system aims to scale to large numbers of autonomous vehicles by distributing sensing and control - vehicles only need to sense their environment and follow path instructions from the remote server.
Innovative system for autonomous charging of Road toll and parking fee.Abraham Paul
This document proposes an innovative system for uniformly charging road tolls and parking fees using wireless technology and GPS networks. The system would replace physical toll booths and parking tickets. A tamper-proof device in each vehicle would use GPS to track location and charge usage-based fees. Fees could vary by location, time of day, and vehicle type. The system aims to streamline fee collection while preventing non-compliance through continuous monitoring. It could generate substantial revenue from road/parking fees as well as value-added services.
The Parking Availability Network is a proposed system that uses sensors embedded in parking spaces and vehicles to track parking availability across a city. Static sensors mark spaces and provide information like occupancy. Mobile sensors in vehicles scan static sensors to tag spaces as occupied or not. This creates a map of parking availability that is integrated with vehicle navigation to help drivers find spaces and reduce congestion. The system also enables dynamic pricing to encourage use of less popular spaces.
This document proposes a novel three-tier vehicle cloud architecture to provide real-time services for cloud computing enabled vehicle networks. The three tiers include the device level, communication level, and service level. The device level includes sensors that can form an in-vehicle body area sensor network. The communication level allows vehicle-to-vehicle and vehicle-to-infrastructure communication. The service level provides context-based, communication-based, and customized services using cloud computing, such as real-time road traffic monitoring and driver healthcare monitoring. The architecture aims to improve safety, convenience, and comfort for drivers.
Traffic Congestion Prediction using Deep Reinforcement Learning in Vehicular ...IJCNCJournal
In recent years, a new wireless network called vehicular ad-hoc network (VANET), has become a popular research topic. VANET allows communication among vehicles and with roadside units by providing information to each other, such as vehicle velocity, location and direction. In general, when many vehicles likely to use the common route to proceed to the same destination, it can lead to a congested route that should be avoided. It may be better if vehicles are able to predict accurately the traffic congestion and then avoid it. Therefore, in this work, the deep reinforcement learning in VANET to enhance the ability to predict traffic congestion on the roads is proposed. Furthermore, different types of neural networks namely Convolutional Neural Network (CNN), Multilayer Perceptron (MLP) and Long Short-Term Memory (LSTM) are investigated and compared in this deep reinforcement learning model to discover the most effective one. Our proposed method is tested by simulation. The traffic scenarios are created using traffic simulator called Simulation of Urban Mobility (SUMO) before integrating with deep reinforcement learning model. The simulation procedures, as well as the programming used, are described in detail. The performance of our proposed method is evaluated using two metrics; the average travelling time delay and average waiting time delay of vehicles. According to the simulation results, the average travelling time delay and average waiting time delay are gradually improved over the multiple runs, since our proposed method receives feedback from the environment. In addition, the results without and with three different deep learning algorithms, i.e., CNN, MLP and LSTM are compared. It is obvious that the deep reinforcement learning model works effectively when traffic density is neither too high nor too low. In addition, it can be concluded that the effective algorithms for traffic congestion prediction models in descending order are MLP, CNN, and LSTM, respectively.
Online/Offline Lane Change Events Detection AlgorithmsFeras Tanan
Abstract—in this paper, We are presenting two algorithms
for lane change detection. The first one is used
for online detection (real-time detection) with accuracy of
85% and the other one is used for offline detection with
accuracy of 95%. The main purpose of the offline detection
algorithm is to find at which GPS locations the number
of happened left/right lane changes.
For the purpose of these algorithms we used the
”crowd-sensing” approach which means that the sensors of
different mobile devices that were fixed in different cars
are the sources of input data for the above mentioned
algorithms. Specifically speaking, we used Accelerometer
and Gyroscope sensors. We also presented an algorithm
for blinker pattern extraction using the microphone sensor.
Keywords: Pattern Extraction, Lane Change detection,
Accelerometer, Gyroscope and Crowd Sensing
The document summarizes an innovation workshop held by ADM. It discusses establishing an innovation ecosystem and funnel management. Key points include:
- Jan Dilis presented on the innovation funnel and how it can stifle innovation by allowing little room for failure.
- The group will work collaboratively until April 18th to develop a case study on an innovation ecosystem for ADM aligned with its business goals.
- Tasks are assigned with deadlines to define the ecosystem, analyze ADM's innovation needs, and propose changes to create an innovative culture.
SharePoint 2013 Enterprise Mobile Strategy - London - Joel OlesonJoel Oleson
SharePoint 2013 Enterprise Mobile Strategy
Delivered by: Joel Oleson
Audience: Business, Architect
So much is changing every day with Microsoft's support for mobile devices with apps for iPads, iPhones, Android phones and tablets, and new Windows Phone devices. With apps SharePoint Online and Office Online, there's a lot to keep track of and understand. In this class, we'll dig into the latest releases of these apps to understand both support and function. We'll also look at Responsive Web Design as a mechanism to support SharePoint for mobile. Is Word, Excel, and PowerPoint good enough on the iPad? The answer is "yes" and we'll help you understand how to ensure you have the right strategy for licensing in addition to taking advantage of the best of what Microsoft is releasing. If you think you knew SharePoint and Mobile, think again!
Mobile App Development with WordPress dataStephen G
Slides talking about using Appcelerator Titanium to write iOS and Android apps written in JavaScript while using a WordPress site as its datasource. Talk given at WordCamp Miami on March 5th
Stephen Gilboy presented on creating web-based mobile apps with ASP.NET, HTML5, and jQuery Mobile. He discussed how jQuery Mobile simplifies creating mobile web apps that work across platforms by handling page transitions and responsive design. He demonstrated consuming JSON data with jQuery templating to populate pages, theming apps from the web.config, and going native with PhoneGap. The presentation provided an overview of building robust mobile apps using existing web development skills.
This document provides an overview and instructions for using a mobile app to help win and keep real estate clients. The app allows users to search for homes, see client wish lists, and share the app through social media and scripts. The goals are to keep clients loyal, save time, and demonstrate value through easy home searches and client-focused features. Instructions are given to explore the app, share it on Facebook, and develop plans and scripts for promoting the app to sellers, buyers, and others.
The document describes a proposed smart parking system that uses wireless sensor networks, embedded web servers, a central web server, and a mobile phone application to help drivers find available parking spaces. Wireless sensor nodes deployed in each parking spot detect occupancy and report it in real-time to embedded web servers. This data is then sent to a central web server which displays current availability and allows reservations via mobile apps. The system aims to more efficiently guide drivers to vacant spots and reduce traffic from drivers searching for parking.
The document describes a proposed smart parking system that uses wireless sensor networks and mobile applications to help drivers find available parking spaces. Sensor nodes deployed in each parking spot detect occupancy and report this information to an embedded web server and central web server in real-time. Drivers can view available spaces on their mobile devices and reserve spots through the reservation-based smart parking system. The system is intended to reduce traffic from drivers searching for parking and guide them to available spots, improving traffic flow and convenience.
Real time vehicle counting in complex scene for traffic flow estimation using...Journal Papers
This document presents a multi-level convolutional neural network (mCNN) framework for real-time vehicle counting and classification in complex traffic scenes. The mCNN framework includes five main modules: pre-processing, object detection, tracking, object classification, and quantification. In the pre-processing stage, images are cropped to remove irrelevant details. A CNN is then used for initial object detection and pre-classification. Detected objects are tracked across frames and a second CNN is used for refined classification before vehicle counts are generated. The mCNN framework is tested on 585 minutes of highway video and achieves an average vehicle counting accuracy of 97.53% and weighted average counting with classification accuracy of 91.5%, demonstrating its effectiveness for real-time
With growing, Car parking increases with the number of car users. With the increased use of smartphones and their applications, users prefer mobile phone-based solutions. This paper proposes the Smart Parking Management System (SPMS) that depends on Arduino parts, Android applications, and based on IoT. This gave the client the ability to check available parking spaces and reserve a parking spot. IR sensors are utilized to know if a car park space is allowed. Its area data are transmitted using the WI-FI module to the server and are recovered by the mobile application which offers many options attractively and with no cost to users and lets the user check reservation details. With IoT technology, the smart parking system can be connected wirelessly to easily track available locations.
With growing, Car parking increases with the number of car users. With the increased use of smartphones
and their applications, users prefer mobile phone-based solutions. This paper proposes the Smart Parking
Management System (SPMS) that depends on Arduino parts, Android applications, and based on IoT. This
gave the client the ability to check available parking spaces and reserve a parking spot. IR sensors are
utilized to know if a car park space is allowed. Its area data are transmitted using the WI-FI module to the
server and are recovered by the mobile application which offers many options attractively and with no cost
to users and lets the user check reservation details. With IoT technology, the smart parking system can be
connected wirelessly to easily track available locations.
This document summarizes a research paper on a smart parking management system that uses IoT technology. The system uses infrared sensors to detect available parking spaces. It transmits parking availability data via Wi-Fi to a server, which then provides the information to a mobile app. The app allows users to check for and reserve available spaces conveniently and free of cost. The system aims to help users more efficiently find parking and reduce traffic and fuel consumption by eliminating unnecessary driving to locate spots. It integrates technologies like Arduino, Android apps, infrared sensors, and cloud computing within an IoT framework.
This document lists 90 projects related to embedded systems and computer vision. The projects cover topics like vehicle detection, face recognition, human detection, eye tracking, speech recognition, wireless sensor networks, and more. The projects are aimed at applications such as surveillance, robotics, automotive, smart homes, and medical devices.
A cloud based smart-parking system basedAmjad Zahid
This document summarizes a research paper on a proposed cloud-based smart parking system based on Internet-of-Things technologies. The proposed system uses sensors in each parking space to monitor occupancy and sends this data to a central cloud server. The cloud server then calculates parking costs based on distance and availability, and provides users with recommendations for available spaces. The system aims to improve the probability of successful parking and minimize user waiting times. The researchers implemented a prototype of the system using Arduino sensors and a smartphone interface to demonstrate feasibility.
A Cloud-Based Smart-Parking System Based on Internet-of-Things TechnologiesKamal Spring
This document summarizes a research paper on a proposed cloud-based smart parking system based on Internet-of-Things technologies. The proposed system uses sensors and wireless networks to collect parking availability data from each parking area. It then calculates parking costs based on distance and availability to recommend available spaces to users. The system was tested in a simulation and implemented in the real world. The results showed the system helped improve the probability of finding parking and minimized user waiting times.
The document describes a parking space counter project developed by a team of 4 students under the guidance of Mrs. Sujakumari N R. The project utilizes Python and OpenCV to create an automated system for counting available parking spaces in real-time by analyzing video feeds and detecting vehicles. The system is intended to improve parking management and enhance user experience by providing accurate information on parking availability. Key modules included video acquisition, vehicle detection and tracking, occupancy analysis and counting, and a user interface to display results.
This document proposes a smart city surveillance system that utilizes vehicle-mounted cameras and sensors to crowdsource real-time data about urban events and conditions. Vehicles would collect image and location data using cameras and GPS and upload it to a cloud server. The server would store the data and make it accessible to the public. The system aims to provide detailed, efficient monitoring of cities to benefit residents and officials. It was tested and shown to perform well under increasing workload.
The document describes a proposed smart parking system called D-PARK that uses Bluetooth Low Energy (BLE) beacons for high-resolution localization of parking spots. It analyzes sensor and signal data from mobile devices to determine user and vehicle status for parking services. The system achieves 95% accuracy in locating a parking spot within the second guess using BLE beacon signals analyzed at different scanning intervals. It also detects user intent through status sensing and cloud analysis to provide an improved parking experience.
Connected Lives: Where Smart Vehicles Meet the Intelligent RoadCognizant
The digital highway promises to enable an ever-expanding ecosystem encompassing intelligent transportation systems, smart cities and logistics systems, optimizing productivity and performance for businesses and individuals.
Advanced Car Parking System with GSM Supported Slot MessengerIOSR Journals
This document describes an advanced car parking system that uses RFID, sensors, a PIC controller, conveyor belts, motors and a GSM module. The system automatically identifies empty parking slots and parks cars in a multi-level parking structure. It calculates parking fees based on time and can send SMS messages with available slot information. The system aims to make parking more efficient and reduce congestion compared to traditional methods. It summarizes the system design, architecture, workflow and concludes the system is a promising solution for modern parking challenges.
This document describes an advanced car parking system that uses RFID, sensors, a PIC controller, conveyor belts, motors and a GSM module. The system automatically identifies empty parking slots and parks cars in a multi-level parking structure. It calculates parking fees based on time and deducts payments automatically. The GSM module allows users to check slot availability via SMS before arriving. The system aims to improve efficiency over traditional parking and reduce congestion.
SharePoint 2013 Enterprise Mobile Strategy - London - Joel OlesonJoel Oleson
SharePoint 2013 Enterprise Mobile Strategy
Delivered by: Joel Oleson
Audience: Business, Architect
So much is changing every day with Microsoft's support for mobile devices with apps for iPads, iPhones, Android phones and tablets, and new Windows Phone devices. With apps SharePoint Online and Office Online, there's a lot to keep track of and understand. In this class, we'll dig into the latest releases of these apps to understand both support and function. We'll also look at Responsive Web Design as a mechanism to support SharePoint for mobile. Is Word, Excel, and PowerPoint good enough on the iPad? The answer is "yes" and we'll help you understand how to ensure you have the right strategy for licensing in addition to taking advantage of the best of what Microsoft is releasing. If you think you knew SharePoint and Mobile, think again!
Mobile App Development with WordPress dataStephen G
Slides talking about using Appcelerator Titanium to write iOS and Android apps written in JavaScript while using a WordPress site as its datasource. Talk given at WordCamp Miami on March 5th
Stephen Gilboy presented on creating web-based mobile apps with ASP.NET, HTML5, and jQuery Mobile. He discussed how jQuery Mobile simplifies creating mobile web apps that work across platforms by handling page transitions and responsive design. He demonstrated consuming JSON data with jQuery templating to populate pages, theming apps from the web.config, and going native with PhoneGap. The presentation provided an overview of building robust mobile apps using existing web development skills.
This document provides an overview and instructions for using a mobile app to help win and keep real estate clients. The app allows users to search for homes, see client wish lists, and share the app through social media and scripts. The goals are to keep clients loyal, save time, and demonstrate value through easy home searches and client-focused features. Instructions are given to explore the app, share it on Facebook, and develop plans and scripts for promoting the app to sellers, buyers, and others.
The document describes a proposed smart parking system that uses wireless sensor networks, embedded web servers, a central web server, and a mobile phone application to help drivers find available parking spaces. Wireless sensor nodes deployed in each parking spot detect occupancy and report it in real-time to embedded web servers. This data is then sent to a central web server which displays current availability and allows reservations via mobile apps. The system aims to more efficiently guide drivers to vacant spots and reduce traffic from drivers searching for parking.
The document describes a proposed smart parking system that uses wireless sensor networks and mobile applications to help drivers find available parking spaces. Sensor nodes deployed in each parking spot detect occupancy and report this information to an embedded web server and central web server in real-time. Drivers can view available spaces on their mobile devices and reserve spots through the reservation-based smart parking system. The system is intended to reduce traffic from drivers searching for parking and guide them to available spots, improving traffic flow and convenience.
Real time vehicle counting in complex scene for traffic flow estimation using...Journal Papers
This document presents a multi-level convolutional neural network (mCNN) framework for real-time vehicle counting and classification in complex traffic scenes. The mCNN framework includes five main modules: pre-processing, object detection, tracking, object classification, and quantification. In the pre-processing stage, images are cropped to remove irrelevant details. A CNN is then used for initial object detection and pre-classification. Detected objects are tracked across frames and a second CNN is used for refined classification before vehicle counts are generated. The mCNN framework is tested on 585 minutes of highway video and achieves an average vehicle counting accuracy of 97.53% and weighted average counting with classification accuracy of 91.5%, demonstrating its effectiveness for real-time
With growing, Car parking increases with the number of car users. With the increased use of smartphones and their applications, users prefer mobile phone-based solutions. This paper proposes the Smart Parking Management System (SPMS) that depends on Arduino parts, Android applications, and based on IoT. This gave the client the ability to check available parking spaces and reserve a parking spot. IR sensors are utilized to know if a car park space is allowed. Its area data are transmitted using the WI-FI module to the server and are recovered by the mobile application which offers many options attractively and with no cost to users and lets the user check reservation details. With IoT technology, the smart parking system can be connected wirelessly to easily track available locations.
With growing, Car parking increases with the number of car users. With the increased use of smartphones
and their applications, users prefer mobile phone-based solutions. This paper proposes the Smart Parking
Management System (SPMS) that depends on Arduino parts, Android applications, and based on IoT. This
gave the client the ability to check available parking spaces and reserve a parking spot. IR sensors are
utilized to know if a car park space is allowed. Its area data are transmitted using the WI-FI module to the
server and are recovered by the mobile application which offers many options attractively and with no cost
to users and lets the user check reservation details. With IoT technology, the smart parking system can be
connected wirelessly to easily track available locations.
This document summarizes a research paper on a smart parking management system that uses IoT technology. The system uses infrared sensors to detect available parking spaces. It transmits parking availability data via Wi-Fi to a server, which then provides the information to a mobile app. The app allows users to check for and reserve available spaces conveniently and free of cost. The system aims to help users more efficiently find parking and reduce traffic and fuel consumption by eliminating unnecessary driving to locate spots. It integrates technologies like Arduino, Android apps, infrared sensors, and cloud computing within an IoT framework.
This document lists 90 projects related to embedded systems and computer vision. The projects cover topics like vehicle detection, face recognition, human detection, eye tracking, speech recognition, wireless sensor networks, and more. The projects are aimed at applications such as surveillance, robotics, automotive, smart homes, and medical devices.
A cloud based smart-parking system basedAmjad Zahid
This document summarizes a research paper on a proposed cloud-based smart parking system based on Internet-of-Things technologies. The proposed system uses sensors in each parking space to monitor occupancy and sends this data to a central cloud server. The cloud server then calculates parking costs based on distance and availability, and provides users with recommendations for available spaces. The system aims to improve the probability of successful parking and minimize user waiting times. The researchers implemented a prototype of the system using Arduino sensors and a smartphone interface to demonstrate feasibility.
A Cloud-Based Smart-Parking System Based on Internet-of-Things TechnologiesKamal Spring
This document summarizes a research paper on a proposed cloud-based smart parking system based on Internet-of-Things technologies. The proposed system uses sensors and wireless networks to collect parking availability data from each parking area. It then calculates parking costs based on distance and availability to recommend available spaces to users. The system was tested in a simulation and implemented in the real world. The results showed the system helped improve the probability of finding parking and minimized user waiting times.
The document describes a parking space counter project developed by a team of 4 students under the guidance of Mrs. Sujakumari N R. The project utilizes Python and OpenCV to create an automated system for counting available parking spaces in real-time by analyzing video feeds and detecting vehicles. The system is intended to improve parking management and enhance user experience by providing accurate information on parking availability. Key modules included video acquisition, vehicle detection and tracking, occupancy analysis and counting, and a user interface to display results.
This document proposes a smart city surveillance system that utilizes vehicle-mounted cameras and sensors to crowdsource real-time data about urban events and conditions. Vehicles would collect image and location data using cameras and GPS and upload it to a cloud server. The server would store the data and make it accessible to the public. The system aims to provide detailed, efficient monitoring of cities to benefit residents and officials. It was tested and shown to perform well under increasing workload.
The document describes a proposed smart parking system called D-PARK that uses Bluetooth Low Energy (BLE) beacons for high-resolution localization of parking spots. It analyzes sensor and signal data from mobile devices to determine user and vehicle status for parking services. The system achieves 95% accuracy in locating a parking spot within the second guess using BLE beacon signals analyzed at different scanning intervals. It also detects user intent through status sensing and cloud analysis to provide an improved parking experience.
Connected Lives: Where Smart Vehicles Meet the Intelligent RoadCognizant
The digital highway promises to enable an ever-expanding ecosystem encompassing intelligent transportation systems, smart cities and logistics systems, optimizing productivity and performance for businesses and individuals.
Advanced Car Parking System with GSM Supported Slot MessengerIOSR Journals
This document describes an advanced car parking system that uses RFID, sensors, a PIC controller, conveyor belts, motors and a GSM module. The system automatically identifies empty parking slots and parks cars in a multi-level parking structure. It calculates parking fees based on time and can send SMS messages with available slot information. The system aims to make parking more efficient and reduce congestion compared to traditional methods. It summarizes the system design, architecture, workflow and concludes the system is a promising solution for modern parking challenges.
This document describes an advanced car parking system that uses RFID, sensors, a PIC controller, conveyor belts, motors and a GSM module. The system automatically identifies empty parking slots and parks cars in a multi-level parking structure. It calculates parking fees based on time and deducts payments automatically. The GSM module allows users to check slot availability via SMS before arriving. The system aims to improve efficiency over traditional parking and reduce congestion.
IRJET- Smart Bus Ticket System using IoT TechnologyIRJET Journal
This document proposes a smart bus ticket system using IoT technology to improve the reliability of public transportation. It involves collecting real-time location data from buses using devices like e-ticketing systems or Android tablets, transmitting the data using MQTT protocol to a scalable IoT backend, and making the location data accessible to users through APIs and mobile/web applications. The system aims to reduce wait times at bus stops by providing estimated arrival times based on current traffic conditions.
Techniques for Smart Traffic Control: An In-depth ReviewEditor IJCATR
Inadequate space and funds for the construction of new roads and the steady increase in number of vehicles has prompted
scholars to investigate other solutions to traffic congestion. One area gaining interest is the use of smart traffic control systems (STCS)
to make traffic routing decisions. These systems use real time data and try to mimic human reasoning thus prove promising in vehicle
traffic control and management. This paper is a review on the motivations behind the emergence of STCS and the different types of
these systems in use today for road traffic management. They include – fuzzy expert systems (FES), artificial neural networks (ANN)
and wireless sensor networks (WSN). We give an in depth study on the design, benefits and limitations of each technique. The paper
cites and analyses a number of successfully tested and implemented STCS. From these reviews we are able to derive comparisons of
the STCS discussed in this paper. For instance, for a learning or adaptive system, ANN is the best approach; for a system that just
routes traffic based on real time data and does not need to derive any data patterns afterwards, then FES is the best approach; for a
cheaper alternative to the FES, then WSN is the least costly approach. All prove effective in traffic control and management with
respect to the context in which each of them is used.
Real time vehicle counting in complex scene for traffic flow estimation using...Conference Papers
This document proposes a multi-level convolutional neural network (mCNN) framework for real-time vehicle counting and classification in complex traffic scenes. The framework includes five modules: pre-processing, object detection using SSD and YOLO models, tracking using Kalman filters, vehicle classification using Inception network, and quantification to provide counting results. The framework is tested on over 585 minutes of highway video from four cameras, achieving 97.53% average counting accuracy and 90.2% weighted average accuracy for counting with classification.
This document proposes a smart parking system using IoT that automates parking and payment using sensors, cameras, and an Android application. The system uses ultrasonic sensors and a USB camera with a Raspberry Pi to detect vehicles and read their license plates upon entry and exit. It matches plates to reserved spots in a database to open barriers. Users can reserve spots and pay through the Android app, which also provides parking location and availability. This system aims to reduce congestion from drivers searching for spots by allowing drivers to locate and reserve spaces remotely. It collects usage data that could help parking owners improve operations based on trends. The system is presented as a solution to issues like inefficient parking searches, lack of availability information, and illegal parking.
Similar to Technology Entrepreneurship Mcity OEP report (20)
How to Make a Field Mandatory in Odoo 17Celine George
In Odoo, making a field required can be done through both Python code and XML views. When you set the required attribute to True in Python code, it makes the field required across all views where it's used. Conversely, when you set the required attribute in XML views, it makes the field required only in the context of that particular view.
How to Setup Warehouse & Location in Odoo 17 InventoryCeline George
In this slide, we'll explore how to set up warehouses and locations in Odoo 17 Inventory. This will help us manage our stock effectively, track inventory levels, and streamline warehouse operations.
LAND USE LAND COVER AND NDVI OF MIRZAPUR DISTRICT, UPRAHUL
This Dissertation explores the particular circumstances of Mirzapur, a region located in the
core of India. Mirzapur, with its varied terrains and abundant biodiversity, offers an optimal
environment for investigating the changes in vegetation cover dynamics. Our study utilizes
advanced technologies such as GIS (Geographic Information Systems) and Remote sensing to
analyze the transformations that have taken place over the course of a decade.
The complex relationship between human activities and the environment has been the focus
of extensive research and worry. As the global community grapples with swift urbanization,
population expansion, and economic progress, the effects on natural ecosystems are becoming
more evident. A crucial element of this impact is the alteration of vegetation cover, which plays a
significant role in maintaining the ecological equilibrium of our planet.Land serves as the foundation for all human activities and provides the necessary materials for
these activities. As the most crucial natural resource, its utilization by humans results in different
'Land uses,' which are determined by both human activities and the physical characteristics of the
land.
The utilization of land is impacted by human needs and environmental factors. In countries
like India, rapid population growth and the emphasis on extensive resource exploitation can lead
to significant land degradation, adversely affecting the region's land cover.
Therefore, human intervention has significantly influenced land use patterns over many
centuries, evolving its structure over time and space. In the present era, these changes have
accelerated due to factors such as agriculture and urbanization. Information regarding land use and
cover is essential for various planning and management tasks related to the Earth's surface,
providing crucial environmental data for scientific, resource management, policy purposes, and
diverse human activities.
Accurate understanding of land use and cover is imperative for the development planning
of any area. Consequently, a wide range of professionals, including earth system scientists, land
and water managers, and urban planners, are interested in obtaining data on land use and cover
changes, conversion trends, and other related patterns. The spatial dimensions of land use and
cover support policymakers and scientists in making well-informed decisions, as alterations in
these patterns indicate shifts in economic and social conditions. Monitoring such changes with the
help of Advanced technologies like Remote Sensing and Geographic Information Systems is
crucial for coordinated efforts across different administrative levels. Advanced technologies like
Remote Sensing and Geographic Information Systems
9
Changes in vegetation cover refer to variations in the distribution, composition, and overall
structure of plant communities across different temporal and spatial scales. These changes can
occur natural.
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An import error occurs when a program fails to import a module or library, disrupting its execution. In languages like Python, this issue arises when the specified module cannot be found or accessed, hindering the program's functionality. Resolving import errors is crucial for maintaining smooth software operation and uninterrupted development processes.
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it describes the bony anatomy including the femoral head , acetabulum, labrum . also discusses the capsule , ligaments . muscle that act on the hip joint and the range of motion are outlined. factors affecting hip joint stability and weight transmission through the joint are summarized.
2. Fundamental Problem
Objetivo del Proyecto
□ Mobility is a fundamental problem in our cities environment
□ According to a study by the MIT in 2006 in New York, 45% of Manhattan traffic is generated by cars traveling
to find parking
2
3. Concept
Descripción de la idea
□ The main idea of the project is to create a sensor network that can be modularly scaled with applications
that will improve the mobility of citizens in the city
Intelligent parking Public Transport
Intelligent traffic
spaces optimization and
management system
management system information system
3
4. IntelligentProyecto spaces management system
Objetivo del parking
□ The first application that we will develop is the Intelligent parking spaces management system
□ Using a wireless sensor network the system will generate a map in real time in certain areas with a high level
of city vehicles that will allow to locate free parking on the surface, indicating drivers equipped with mobile
GPS devices who activate the role of parking, the nearest place to park
4
5. IntelligentProyecto spaces management system
Objetivo del parking
□ The system will be updated in real time so that if one free spot is occupied it will redirect the user of the
system to the next closest parking space to avoid that 2 drivers are directed towards the same spot
□ System efficiency will increase as more drivers use it as it will never lead two drivers to the same square free
spot
5
6. Intelligent parking spaces management system
□ The project will be supplemented with the information from the underground parking area, providing the
user of the application to be guided to those that are free
6
7. Intelligent traffic management system
□ By using the real time traffic data from Google Maps it will allow citizens to avoid areas with heavy traffic and
reach the parking in the shortest time possible
7
8. Intelligent parking spaces management system
Descripción de la idea
□ Idea Concept
The citizen will know in real
time the congestion zones
where he is going to
The platform will analyze
The system will guide the
The sensors will monitor the data and create a real-
citizens to the nearest
the parking spaces time map of available
parking spot by GPS
parking spots
It will send the The controller will
It will send the
information to know what parking
information to the
citizens and space has been
Platform
controllers occupied
8
9. Public transportation optimization and information system
□ By using the position sensors on public transport you can know in real time:
The situation of taxis, taxi stops and the direction in which they move in order to intercept them. This
can be enhanced with a call application to the taxi company
The situation of urban buses, and the estimated time to destination, showing their exact location on the
screen of the device
The Platform will analyze the data and generate reports in real time to the company drivers so they can
fit their expectations based on other transports and avoid oversaturation in certain areas
The integration of these data with the information from Google Maps about stops, train stations, subway
lines, will provide citizens the broadest choices of mobility in the city
9
10. Market Analysis
Descripción de la idea
□ The global market for wireless sensor networks has reach about 4.6 billion dollars in 2011 from 500 million
dollars that the market was in 2007 according to the ON World potential market analysis
□ The aim is to implement the solution in Spanish cities before scaling it to the rest of the world
□ Given the need for the existence of a critical mass of users in order to assess the feasibility of the solution the
potential market in Spain adheres according to the National Institute of Statistics to 145 municipalities with a
population over 50,000 inhabitants
□ The prototype will be implemented in Madrid
According to the INE data the number of vehicles in the city of Madrid is 1,990,585
Spain in 2009 reached the figure of 9.709.023 smartphones according to the data from the consulting firm
Comscore. Which involves a penetration of 28% for those mobiles
Extrapolating that data to Madrid would be reached a figure of 557,363 potential buyers
in the city of Madrid for mobility applications
10
11. Market Analysis – Cost Analysis
Descripción de la idea
□ The results are estimated as it follows:
The investments made in the project will be offset by the sale of applications for citizens and licenses to
company's
From a potential demand of 557.363 users, are estimated to be early adopters
about 60.000 users
With the diffusion and promotion of the product is expected to reach 40% of the potential target within
2 years which would mean 222.945 users of the application by that time
At an estimated price of 11€ per application with an annual renewable fee it will generate profits
within 3 years, offsetting the investment in 7 years
11
12. Market Analysis – Cost Analysis
Income 2012 2013 2014 2015 2016
Number of the users of the application 0 60000 220000 380000 420000
Price Application and maintenance fee 0 0 11 11 12
Net income 0 0 2420000 4180000 5040000
Costs 2011 2012 2013 2014 2015
Areas parameterization 268323 1325323 0 0 0
Wireless Sensor Network construction 123423 3235673 0 0 0
Wireless Sensor Network maintenance 0 0 163243 362344 675444
Comunications 1453 123543 323534 562344 623756
Salaries 1098385 982343 823323 762431 621473
Publicity 0 234536 672323 432213 214215
Total Costs 1491584 5901418 1982423 2119332 2134888
Results -1491584 -5901418 437577 2060668 2905112
14. MarketingProyecto
Objetivo del Strategy
□ License Model
Every time a smartphone or GPS is sold with our license the
application or data will come pre-installed for it s use
15. MarketingProyecto
Objetivo del Strategy
□ App Model
Our marketing Strategy will be local focused
We will focus our efforts in going where the customer is so they can see our app exists, and
download it (parking spots, bus stops, taxis, subways)
Parking App Public Transport App
16. PrototypeProyecto
Objetivo del
□ Our prototype will be build in a small zone of Madrid with a high traffic density and lot of parking needs
Video demo at venture lab &
http://www.youtube.com/watch?v=TcnnCpSgvX8
17. Prototypede la idea
Descripción
□ In order to achieve the objectives and scope of the idea we will proceed to:
The creation of a platform and an information system that facilitates the creation of modular solutions
for smart sensor networks
The development of a highly scalable system that can support massive networks, being able to sustain in
a long-term thousands of sensors and actuators
The adaptation of different models of sensors and actuators to the application requirements
Data Analysis
Events Analysis
State of nodes
Network Monitoring Application A
Sensor Network A
Georeferencing Engine
Planning system
Application B
Sensor Network B
Monitoring System
Sensor Network C
17
18. PrototypeProyecto
Objetivo del
□ Means necessary to carry out the idea:
SENSOR BOARD
It will allow the integration of event plates as well as communications modules
COMMUNICATION MODULES
Communication module protocols:
802.15.4, Zigbee-Pro, RF
They will allow the creation of the mesh network of sensors
GSM / GPRS Communication module
It will allow to make / receive communications, internet connection via TCP /
IP sockets and UDP / IP, SMTP service and FTP service
GPS positioning module
It will define the latitude, longitude, altitude, speed, heading, date / time of
the node
19. PrototypeProyecto
Objetivo del
□ Means necessary to carry out the idea:
EVENT BOARD
I will allow the capture of information from abroad to integrate it into the sensor board
GATEWAY
It will transmit the information received by the nodes to the central servers so that the
information is processed by the information system
CE NTRAL SERVERS
They will allow the storage of data to be processed by the information system
20. Funding Proyecto
Objetivo del
□ As a project that is part of the smart cities initiative we intend to present it to the
seventh framework programme
□ That will allow us to cooperate with other European companies, giving us the possibility
to expand the project to other European cities in a short term once the prototype is
build
□ Once the prototype is build, we will present it to the Industrial Technology
Development Centre so we can get the necessary funds to expand it to other zones and
cities
□ That, will give us access to the Technology Fund from European Union FEDER funds
dedicated to the promotion of R&D projects in EU