Four trends of intelligent transportation system technology -- C&T RF Antenna...Antenna Manufacturer Coco
The overall trend of the development of intelligent transportation technology mainly includes four aspects: accurate perception of traffic operation situation and intelligent control, intelligent vehicle control and coordinated control of pedestrians, vehicles, and roads, and integrated intelligent transportation services based on mobile Internet development of.
Solving the problem of nano-technological focused development of quantum computer allows radically change all processes and phenomena in the macrocosm, which develops in the form of cyberspace of the planet and It uses global positioning and navigation, as well as mobile gadgets and the Internet for improving the quality and safety of vehicle movement and minimization the time and costs. The innovative idea is using a virtual cloud space for vehicle management.
Four trends of intelligent transportation system technology -- C&T RF Antenna...Antenna Manufacturer Coco
The overall trend of the development of intelligent transportation technology mainly includes four aspects: accurate perception of traffic operation situation and intelligent control, intelligent vehicle control and coordinated control of pedestrians, vehicles, and roads, and integrated intelligent transportation services based on mobile Internet development of.
Solving the problem of nano-technological focused development of quantum computer allows radically change all processes and phenomena in the macrocosm, which develops in the form of cyberspace of the planet and It uses global positioning and navigation, as well as mobile gadgets and the Internet for improving the quality and safety of vehicle movement and minimization the time and costs. The innovative idea is using a virtual cloud space for vehicle management.
Innovations in London's Transport: Big Data for a Better Customer ServiceGovnet Events
Presentation on Innovations in London's Transport: Big Data for a Better Customer Service by Andrew Hyman, TFL at HPC and Big Data 2016 in Central London
Air Transport Industry: The future is connected
The combination of connected technology and connected people is helping to reshape the journey for air passengers and, increasingly, their expectations and behavior. Contextual communications via internet-enabled devices and objects will become the enabler for more seamless air travel experiences over the coming years.
For airlines and airports, the focus will be to manage all the physical (and virtual) “objects” that comprise their business ecosystem.
For connected travelers, the Internet of Things (IoT) offers opportunities to link with the air transport industry’s IT ecosystem to manage and personalize their journey from their own smart mobile device, on the ground and in the air.
Grow smarter project kista watson summit 2018_tommy auoja-1IBM Sverige
Avicii på Tele2 arena, Drake på Globen och AIK - Luleå på Hovet bäddar för en trång lördagseftermiddag i Globenområdet... (SVT Nyheter, 1 mars 2014) ...och problemen kvarstår än idag
Talare: Tommy Auoja, Kundansvarig för Offentlig Sektor, Kontaktperson i EU projektet GrowSmarter, IBM
Presentation från Watson Kista Summit 2018
What AI and Machine Learning Can Do for a Smart City Tyrone Systems
Artificial Intelligence and Machine Learning algorithms have increasingly become an integral part of several industries. Now they are making their way to smart city initiatives, intending to automate and advance municipal activities and operations at large.
A smart city has various use cases for AI-driven and IoT-enabled technology, from maintaining a healthier environment to advancing public transport and safety.
By leveraging AI and machine learning algorithms, along with IoT, a city can plan for better smart traffic solutions making sure that inhabitants get from one point to another as safely and efficiently as possible.
Mobiliuz. We make cars smart and connectedMobiliuz
Mobiliuz makes cars smart and connected.
This is the platform, which collects and analyses data from on-board computers of the cars, geolocation, driver’s public profile, weather, time of day, and mass of other info. Mobiliuz - iTunes for the cars - brings unique opportunities to build services from remote diagnostic, to CRM for car services, parking payment, smart insurance, and other products to consumers, business and municipals. It is open to variety of OBD II / GPS trackers and other FMS hardware.
We also develop own hardware - Mobiliuz Tube - local area network server, installed in a car. It enables on-board computer / CAN bus, and any WiFi or bluetooth enabled device in the car or around, to talk to each other and to internet. This opens access to the car for the hardware (HW developers) smartphones, smart wearables, specific equipment or sensors (for emergency services, road police, logistics, etc.) and communicate with outside devices (barriers, road signs and the like).
Machine vision based smart parking system using Internet of ThingsTELKOMNIKA JOURNAL
It is expected that in the next decade, majority of world population will be living in cities.
Better public services and infrastructures in the city are needed to cope with the booming population.
City vehicles that cruising for parking have indirectly causing traffic, making one harder to travel around the
city. Thus, a smart parking system can certainly lays the foundation to build a smart city. This paper
proposed a cost-effective IoT smart parking system to monitor city parking space and provide real-time
parking information to drivers. Moreover, instead of the conventional approach that uses embedded
sensors to detect vehicles in the parking area, camera image and machine vision technology are used to
obtain the parking status. In the prototype, twenty outdoor parking lots are covered using a 5 megapixel
camera connected to Raspberry Pi 3 installed at the 5th floor of the nearby building. Machine vision in this
project that involved motion tracking and Canny edge detection are programmed in Python 2 using
OpenCV technology. Corresponding data is uploaded to an IoT platform called Ubidots for possible
monitoring activity. An Android mobile application is designed for user to download real-time data of
parking information. This paper introduces a low cost smart parking system with the overall detection
accuracy of 96.40%. Also, the mobile application allows users to alert other car owners for any emergency
incidents and double parking blockage. The developed system can provide a platform for users to search
for empty car parking with ease and reduce the traffic issues such as illegal double parking especially in
the urban area.
Smart Car Parking system using GSM Technologydbpublications
In this paper, we present PGS, a Parking Guidance System based on wireless sensor network(WSN) which guides a driver to an available parking lot. The system consists of a WSN based VDS (vehicle detection sub-system) and a management subsystem. The WSN based VDS gathers information on the availability of each parking lot and the management sub-system processes the information and refines them and guides the driver to the available parking lot by controlling a VMS (Variable Messaging System). The paper describes the overall system architecture of PGS from the hardware platform to the application software in the view point of a WSN. We implemented the WSN based VDS of PGS and experimented on the system with several kinds of cars.
Innovations in London's Transport: Big Data for a Better Customer ServiceGovnet Events
Presentation on Innovations in London's Transport: Big Data for a Better Customer Service by Andrew Hyman, TFL at HPC and Big Data 2016 in Central London
Air Transport Industry: The future is connected
The combination of connected technology and connected people is helping to reshape the journey for air passengers and, increasingly, their expectations and behavior. Contextual communications via internet-enabled devices and objects will become the enabler for more seamless air travel experiences over the coming years.
For airlines and airports, the focus will be to manage all the physical (and virtual) “objects” that comprise their business ecosystem.
For connected travelers, the Internet of Things (IoT) offers opportunities to link with the air transport industry’s IT ecosystem to manage and personalize their journey from their own smart mobile device, on the ground and in the air.
Grow smarter project kista watson summit 2018_tommy auoja-1IBM Sverige
Avicii på Tele2 arena, Drake på Globen och AIK - Luleå på Hovet bäddar för en trång lördagseftermiddag i Globenområdet... (SVT Nyheter, 1 mars 2014) ...och problemen kvarstår än idag
Talare: Tommy Auoja, Kundansvarig för Offentlig Sektor, Kontaktperson i EU projektet GrowSmarter, IBM
Presentation från Watson Kista Summit 2018
What AI and Machine Learning Can Do for a Smart City Tyrone Systems
Artificial Intelligence and Machine Learning algorithms have increasingly become an integral part of several industries. Now they are making their way to smart city initiatives, intending to automate and advance municipal activities and operations at large.
A smart city has various use cases for AI-driven and IoT-enabled technology, from maintaining a healthier environment to advancing public transport and safety.
By leveraging AI and machine learning algorithms, along with IoT, a city can plan for better smart traffic solutions making sure that inhabitants get from one point to another as safely and efficiently as possible.
Mobiliuz. We make cars smart and connectedMobiliuz
Mobiliuz makes cars smart and connected.
This is the platform, which collects and analyses data from on-board computers of the cars, geolocation, driver’s public profile, weather, time of day, and mass of other info. Mobiliuz - iTunes for the cars - brings unique opportunities to build services from remote diagnostic, to CRM for car services, parking payment, smart insurance, and other products to consumers, business and municipals. It is open to variety of OBD II / GPS trackers and other FMS hardware.
We also develop own hardware - Mobiliuz Tube - local area network server, installed in a car. It enables on-board computer / CAN bus, and any WiFi or bluetooth enabled device in the car or around, to talk to each other and to internet. This opens access to the car for the hardware (HW developers) smartphones, smart wearables, specific equipment or sensors (for emergency services, road police, logistics, etc.) and communicate with outside devices (barriers, road signs and the like).
Machine vision based smart parking system using Internet of ThingsTELKOMNIKA JOURNAL
It is expected that in the next decade, majority of world population will be living in cities.
Better public services and infrastructures in the city are needed to cope with the booming population.
City vehicles that cruising for parking have indirectly causing traffic, making one harder to travel around the
city. Thus, a smart parking system can certainly lays the foundation to build a smart city. This paper
proposed a cost-effective IoT smart parking system to monitor city parking space and provide real-time
parking information to drivers. Moreover, instead of the conventional approach that uses embedded
sensors to detect vehicles in the parking area, camera image and machine vision technology are used to
obtain the parking status. In the prototype, twenty outdoor parking lots are covered using a 5 megapixel
camera connected to Raspberry Pi 3 installed at the 5th floor of the nearby building. Machine vision in this
project that involved motion tracking and Canny edge detection are programmed in Python 2 using
OpenCV technology. Corresponding data is uploaded to an IoT platform called Ubidots for possible
monitoring activity. An Android mobile application is designed for user to download real-time data of
parking information. This paper introduces a low cost smart parking system with the overall detection
accuracy of 96.40%. Also, the mobile application allows users to alert other car owners for any emergency
incidents and double parking blockage. The developed system can provide a platform for users to search
for empty car parking with ease and reduce the traffic issues such as illegal double parking especially in
the urban area.
Smart Car Parking system using GSM Technologydbpublications
In this paper, we present PGS, a Parking Guidance System based on wireless sensor network(WSN) which guides a driver to an available parking lot. The system consists of a WSN based VDS (vehicle detection sub-system) and a management subsystem. The WSN based VDS gathers information on the availability of each parking lot and the management sub-system processes the information and refines them and guides the driver to the available parking lot by controlling a VMS (Variable Messaging System). The paper describes the overall system architecture of PGS from the hardware platform to the application software in the view point of a WSN. We implemented the WSN based VDS of PGS and experimented on the system with several kinds of cars.
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.
Application of improved you only look once model in road traffic monitoring ...IJECEIAES
The present research focuses on developing an intelligent traffic management solution for tracking the vehicles on roads. Our proposed work focuses on a much better you only look once (YOLOv4) traffic monitoring system that uses the CSPDarknet53 architecture as its foundation. Deep-sort learning methodology for vehicle multi-target detection from traffic video is also part of our research study. We have included features like the Kalman filter, which estimates unknown objects and can track moving targets. Hungarian techniques identify the correct frame for the object. We are using enhanced object detection network design and new data augmentation techniques with YOLOv4, which ultimately aids in traffic monitoring. Until recently, object identification models could either perform quickly or draw conclusions quickly. This was a big improvement, as YOLOv4 has an astoundingly good performance for a very high frames per second (FPS). The current study is focused on developing an intelligent video surveillance-based vehicle tracking system that tracks the vehicles using a neural network, image-based tracking, and YOLOv4. Real video sequences of road traffic are used to test the effectiveness of the method that has been suggested in the research. Through simulations, it is demonstrated that the suggested technique significantly increases graphics processing unit (GPU) speed and FSP as compared to baseline algorithms.
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Vellore - 632006.
Mobile : +91-9500218218 / 8220150373| land line- 0416- 3552723
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Email : info@shakastech.com | shakastech@gmail.com |
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Accelerate your Kubernetes clusters with Varnish CachingThijs Feryn
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The latest edition of the OT/ICS and IoT security Threat Landscape Report 2024 also covers:
State of global ICS asset and network exposure
Sectoral targets and attacks as well as the cost of ransom
Global APT activity, AI usage, actor and tactic profiles, and implications
Rise in volumes of AI-powered cyberattacks
Major cyber events in 2024
Malware and malicious payload trends
Cyberattack types and targets
Vulnerability exploit attempts on CVEs
Attacks on counties – USA
Expansion of bot farms – how, where, and why
In-depth analysis of the cyber threat landscape across North America, South America, Europe, APAC, and the Middle East
Why are attacks on smart factories rising?
Cyber risk predictions
Axis of attacks – Europe
Systemic attacks in the Middle East
Download the full report from here:
https://sectrio.com/resources/ot-threat-landscape-reports/sectrio-releases-ot-ics-and-iot-security-threat-landscape-report-2024/
State of ICS and IoT Cyber Threat Landscape Report 2024 preview
Real time vehicle detection, tracking and counting using raspberry pi.
1. 2020 – 2021
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Real Time Vehicle Detection, Tracking and Counting Using Raspberry-Pi.
Abstract:
Population explosion leads to an unprecedented increase in the number of physical objects
or vehicles on road. As a result, the number of road accidents increases due to a very heavy
traffic flow. In this paper, traffic flow is monitored by using computer vision paradigm, where
images or sequence of images provides a betterment on the road view. In order to detect
vehicles, monitor and estimate traffic flow using low cost electronic devices, this research
work utilizes camera module of raspberry pi along with Raspberry Pi 3. It also aims to develop
a remote access using raspberry-pi to detect, track and count vehicles only when some
variations occur in the monitored area. The proposed system captures video stream like
vehicles in the monitored area to compute the information and transfer the compressed video
stream for providing video based solution that is mainly implemented in Open CV by Python
Programming. The proposed method is considered as an economical solution for industries
in which cost-effective solutions are developed for traffic management.