Collaboration With HWAcom : Case Study With LED Vision

Collaboration With HWAcom : Case Study With LED Vision

Collaboration With HWAcom : Case Study With LED Vision

Collaboration With HWAcom: Case Study With LED Vision highlights the transformative journey undertaken by these two industry leaders. By combining their expertise, they have revolutionized the way cities function by leveraging cutting-edge LED technology. This case study delves into the collaborative efforts that have led to remarkable outcomes.

ADDRESSING URBANIZATION CHALLENGES: A COLLABORATIVE APPROACH

In the dynamic landscape of Malaysia’s urbanization, HWACom System and LED Vision Sdn Bhd have united to strengthen intelligent transportation systems in Johor Baru. This collaboration is poised to enhance traffic management, alleviate congestion, and fortify the digital infrastructure for safer and more efficient urban mobility.

REVOLUTIONIZING TRAFFIC MANAGEMENT WITH LED VISION’S CTI SOLUTIONS

Unleashing A.I. Power

LED Vision’s CTi solution strategically deploys AI-enabled CCTV cameras and edge mini PCs at critical junctions, connected via 4G connectivity. These devices meticulously collect crucial traffic data, serving as a cornerstone for traffic authorities and controllers to make informed decisions, ultimately contributing to more efficient traffic management.

    Architectural Ingenuity

    The architectural foundation of the CTi solution represents a significant leap forward in intelligent transportation, allowing for real-time data analysis and adaptive strategies to optimize traffic flow.

    PAVING THE WAY FOR THE FUTURE: INTELLIGENT TRANSPORTATION IN MALAYSIA

    The collaborative efforts of HWACom and LED Vision lay the groundwork for the future of intelligent transportation in Malaysia. The integration of advanced traffic control, real-time data analysis, and adaptive strategies is anticipated to revolutionize urban mobility. Moreover, upcoming applications such as V2X based solutions hold the promise of enhancing emergency response capabilities, prioritizing critical vehicles like smart ambulances.

    Intelligent Transportation Systems (ITS)

    Strengthening Foundations with HWACom’s Cyber Monitor

    To fortify the resilience of the ITS infrastructure, a strategic integration with HWACom’s Cyber Monitor system has been implemented. This software-based network management system enhances security and threat detection capabilities, ensuring secure connections and proactively addressing potential system downtime. Cyber Monitor monitors digital IoT devices, edge computers, and traffic light controllers in real-time, providing a crucial layer of protection.

    Cyber Monitor Network Management System

    Synergistic Progress: A Leap into Urban Mobility

    The collaborative synergy between HWACom and LED Vision represents a significant leap forward in enhancing urban mobility and traffic management. Beyond tackling immediate urbanization challenges, this partnership sets the stage for a promising future in intelligent transportation in Malaysia, envisioning cities that are not just smart but also efficient, secure, and tailored for the well-being of all citizens.

    Ipoh’s Traffic Revolution: STARS System’s 51% Flow Boost with AI Innovation

    Ipoh’s Traffic Revolution: STARS System’s 51% Flow Boost with AI Innovation

    Ipoh's Traffic Revolution: STARS System's 51% Flow Boost with AI Innovation

    Ipoh’s Traffic Revolution: STARS System’s 51% Flow Boost with AI Innovation

    Ipoh has introduced the Smart Traffic Light with Intelligence Analytic (STARS), a collaboration between MBI and TM. Using AI, high-definition cameras, and video analytics, STARS optimizes traffic flow, achieving a remarkable 51% improvement during peak hours. The initiative aligns with MBI’s goal to make Ipoh a low-carbon city by 2030.

    STARS is linked to the Ipoh Integrated Operation Centre (IIOC), utilizing Big Data, AI, and 5G. Ipoh is the first northern city to access 5G at 1 GB per second, with plans to add 98 more 5G sites by October. For more information, refer to articles on;

    Intel Iot Kits - AI Powered Traffic

    AI Powered Traffic Management with Intel-Based Edge AI Cameras

    AI Powered Traffic Management with Intel-Based Edge AI Cameras

    LED Vision Pioneer AI-Powered Traffic Management with Intel-Based Edge AI Cameras

    LED Vision Pioneer AI Powered Traffic Management with Intel-Based Edge AI Cameras 

    In an AI traffic management system, data is captured and processed on the edge and then sent to the cloud for additional processing. In the cloud, the historical traffic data is used to model flow dynamics. An AI optimizer then create an optimized traffic control plan. The plan is pushed out to traffic signal controllers in the field, where the edge AI cameras monitor the flow of traffic and send data to the cloud for ongoing optimization.

    Intel Iot Kits - AI Powered Traffic

    Lights Up Malaysia Port with Cutting-Edge LED Solutions

    Lights Up Malaysia Port with Cutting-Edge LED Solutions

    AdvanLED Lights Up Malaysia Port with Cutting-Edge LED Solutions

    MALAYSIA PORT

    One of the Malaysia Port renowned for its cutting-edge facilities, advanced equipment, and comprehensive information technology systems, seamlessly integrates all port users into its operations.

    The port takes pride in delivering dependable, efficient, and state-of-the-art services to major shipping lines and container operators. This commitment ensures that shippers, both domestically and internationally, enjoy extensive connectivity to the global market at Malaysia Port. This integration facilitates the smooth movement of cargoes, providing customers and business partners with a distinct advantage in their operations.

    PROJECT INTRODUCTION

    Description

    1. This Malaysia port established operating for over 23 years since its establishment on 13 March 2000, is embarking on a comprehensive project to upgrade its lighting infrastructure. The existing light fittings in major equipment have become old and worn out, necessitating a modernization effort.

    2. The project is divided into two main divisions. The first division focuses on the primary equipment of the port, namely the quay crane (QC) and rubber-tyred gantry (RTG). To ensure optimal lighting for these critical areas, new LED flood lights have been installed. In this scope of work, a total of 35 sets of QCs and 35 sets of RTGs have been upgraded, resulting in the installation of 557 units of LED Flood Light Fitting (16°) at the QCs and 496 units of LED Flood Light Fitting (45°) at the RTGs

    3. The second division encompasses various areas, including the new engineering workshop, Warehouse DW4, and street lighting within and outside the port which covers Wisma A and B. The wharf area is also covered in this scope of work. To provide efficient illumination in these spaces, LED High Bay Light Fittings, LED Street Light Fittings and LED High Mast Light Fittings have been strategically installed. A total of 426 LED High Bay Light Fittings have been deployed, 271 LED Street Light Fittings positioned both within and outside the port premises and along with 338 LED High Mast Light Fittings installed on 20 poles at the wharf.

    4. By upgrading the lighting infrastructure aimed to enhance visibility, safety, and operational efficiency within its facilities. This project represents a significant investment in modernizing the port’s lighting systems to meet the growing demands of a dynamic and bustling port environment.

    Scope of Work

    1. This port established port with a history spanning over 23 years since its establishment on 13 March 2000, is currently immersed in an all-encompassing initiative to enhance its lighting infrastructure. The existing light fittings on major equipment have reached a state of aging and wear, necessitating a crucial modernization effort.

    2. Breakdown of the activities and documents involved:

      • Project Schedule
      • Sample Simulation
      • Method of Statement (MOS)
      • Manual of related certificates for LED
      • Factory Acceptance Test (FAT)
      • HSE Plan
      • Mobilization and Installation
      • Inspection Test Plan (ITP) and Daily Reports
      • Work completion report
      • Project Claims (Progressively)

    Project Planning Process

    1. Unpredictable weather conditions posed a major challenge, causing disruptions and delays in project tasks. Adjustments to the schedule were essential for maintaining safety and efficiency during installation.

    2. The project’s location within an active port area presented additional hurdles. Work interruptions occurred as the team had to wait for cargo unloading, requiring tools and equipment to be set aside until port activities were completed.

    3. Considering these challenges, the revised completion duration for the project is set at 9 months.

    4. Effective project management and communication with the client facilitated agreement on the adjusted timeline, ensuring the successful and timely completion of the project.

    CHALLENGES

    1. To meet the specific requirements of the port, we had to customize the light fitting brackets for LED Flood Lights and the LED High Mast Light Fitting. Initially, the brackets were made of mild steel, and the mounting holes were at different locations. However, this port requested that stainless steel brackets be painted with epoxy paint for enhanced durability and corrosion resistance. This customization involved sourcing stainless steel materials, applying epoxy paint, and adjusting screw holes to ensure that the brackets met Port’s stringent standards. This solution successfully fulfilled Port’s requirements, reducing installation time and effort while ensuring a seamless fit for the lighting fixtures.

    2. Achieving certain certifications proved challenging. The IEC 62722, IEC 62717, and Neutral Salt Spray Test require 1000 hours to complete, making it a time-consuming process. Certifications like IK09 and IP66 presented challenges as the required quality was niche, making it difficult to find suitable suppliers. Moreover, the customization of components solely for our project resulted in higher costs.

    3. Unforeseen factors, such as adverse weather conditions, the allocation of the port time slots prioritizing ship and container transportation, and festivals, resulted in a delay. The occurrence of festivals added to the challenges, as it affected manpower availability and work schedules. We had to adapt to these circumstances by temporarily suspending work, storing tools and equipment, and resuming installation after the festival period, which further contributed to the overall project timeline.

    4. Various installation challenges were encountered during the project:

    • QC & RTG :
      The light fittings at the QC and RTG are located at an elevated height of above 15m. Thus, to ensure the safety of our workers, our team undergoes comprehensive training such as NIOSH and are taught to strictly adheres to safety protocols especially those outlined in the “Yellow Book”. By following these guidelines and implementing meticulous planning, we prioritize the well-being of our workers and maintain a safe working environment through- out the installation process.
    • High Bay :
      The use of an electrical boom lift was necessary for installation, as this is the requirement posted by the Pot. However, due to the layout of the warehouse, certain areas were inaccessible using this method, requiring alternative solutions to be devised
    • High Mast:
      Adjusting the angle of the high mast lighting to meet the required lux level of 30 poses challenges, demanding precise alignment, coordination, and careful calibration of the lighting fixtures. Furthermore, the busy activities at the wharf and yard provide an obstruction to completing the work.
    • Street Light:
      Power supply issues at this port added complexity to the installation and testing process, requiring additional troubleshooting and coordination with port personnel.

    5. The port’s strict documentation requirements presented an additional challenge. Extensive attention to detail and thorough documentation were necessary to meet their stringent standards and ensure compliance throughout the project.

     

    Summary

    LED Vision Sdn Bhd successfully supplied, delivered, installed, tested, and commissioned LED lights for quay cranes (QC), rubber-tired cranes (RTG), high masts, high bays, and street lights for the port despite the challenges. The upgraded lighting infrastructure has had a positive impact, increasing safety, visibility, and productivity, resulting in client satisfaction. Future collaborations and initiatives are anticipated for further enhancements.

    Adaptive Traffic Control Systems and Methods

    Adaptive Traffic Control Systems and Methods

    Adaptive Traffic Control Systems and Methods

    INTRODUCTION

    A traffic intersection is a location where vehicular traffic going in different directions can proceed in a controlled manner designed to minimize accidents. Intersections with heavy traffic or fast traffic are usually controlled by traffic signals. Most of the traffic signals today can be divided into 2 categories; i.e., fixed time and vehicle actuated (VA).

    Fixed time signals are set to repeat regularly a cycle of red, amber (or yellow), and green lights. Depending upon the traffic intensities at different times of the day, the timings of each phase of the cycle are predetermined. Those predetermined timings that are set to activate according to a schedule are called multiplan.

    By design, multiplan serves only the average peak traffic flow at different time frames based on historical traffic flow volumes. The cycle of red, yellow, and green goes on irrespective of whether on any road, at the time, there is any traffic or not. Traffic in the heavy stream has to stop at the end of the phase, and green time is wasted serving roads with low traffic.

    In conventional VA signals, in-ground loop detectors are placed at each lane for vehicle detection. The timings of the phase and cycle are changed according to traffic demand. While this system reduces the loss of green time by ending the cycle early when the demand is low and extends the green time to serve more traffic in the heavy stream, its range of detection is limited and its accuracy is highly dependent on the number of detectors installed. Aside from the increase in cost for installing more detectors, these in-ground loops also accelerate roadway deterioration, which further increases the cost due to road maintenance.

    As fixed time and VA usually operate within a single intersection, the lack of coordination between adjacent intersections means that vehicles may need to stop at multiple red lights when traveling through a series of nearby intersections. This impedes traffic progression and increases traffic delays.

    A good multi-intersection traffic system design will require each intersection to share traffic information with one another and have their signal timings coordinated and synchronized to produce a continuous traffic flow over several intersections in one main direction, i.e., green wave, thus promoting higher traffic loads, which most of the traffic systems in Malaysia currently lack. To achieve this, a central processing unit or computer is usually needed to process the traffic information gathered across all intersections and decide on generating new instructions to control the traffic lights.

    SASCOO (Step Adaptive Split-Cycle-Offset Optimizer) is an intelligent traffic control system, designed to optimize traffic movement. SASCOO infrastructure (Figure 1) consists of multiple video recording devices, multiple local processing units, and a cloud processing unit.

    When the SASCOO infrastructure is first installed, intelligent cameras are placed at the entrances of every intersection to detect the movements of all vehicles. The local PC at each intersection processes this information and sends this data to the cloud, where SASCOO algorithms are applied and optimal traffic signaling instructions are sent back to the intersections. These instructions determine the duration of green lights and the sequence of traffic movement. This process happens for every traffic light cycle, allowing SASCOO to make real-time decisions and adapt to the ever-changing demands of the traffic flow.

    Video recording devices, i.e., cameras are deployed at each intersection to capture traffic data. Depending on the size of the intersection, extra cameras may be added. There are 2 types of cameras at each intersection, one has a stationary view of the entrance of an intersection, i.e., the area in front and behind the stop line, another one has a 360-degree rotatable view of the intersection. The former is used for capturing vehicular data such as license plate, classification and count, and traffic data such as queue, residual, and occupancy. These data are collected and processed by a local computer before sending them to the cloud for further processing. The latter is used for intersection monitoring purposes.

    The recorded videos are processed in real-time using neural networks that are trained beforehand and all resulting information is stored in the cloud’s database. Vehicle detection that includes vehicle classification and the location of the vehicles is done in the camera using object detection and recognition. Vehicle count and passenger car unit (PCU) are then determined for each respective lane. License plate recognition is done by the local PC using Image-based Sequence Recognition. High-resolution (4K) cameras are used to get the license plate numbers of the vehicles. By matching the license plates across different intersections, the journey time and speed of a vehicle can be estimated. Based on the historical behavior of the intersections, SASCOO algorithm generates a dedicated signal timing plan, i.e., multiplan for each intersection and coordinates the green lights along the arterial roads to produce green wave progressions.

    The other pieces of information provided by the cameras are the queue and residual. The queue is the number of vehicles waiting at the intersection during red. The queue used here refers to the queue that is ready to leave the intersection, i.e., right before the start of green. The residual, on the other hand, refers to the remaining queue at the end of green, i.e., the queuing vehicles that are unable to pass through the intersection after the duration of green. SASCOO algorithm uses this information to make adaptations to the multiplan to meet the latest traffic condition. The offset is the time from when a signal turns green until the succeeding signal turns green along a series of intersections. Compared with a preceding signal, a positive offset means that the succeeding signal turns green later; a negative offset means that the succeeding signal turns green sooner; a zero offset means that both the signals turn green at the same time.

    This offset is adjusted to make the traffic pass through several intersections without the need to stop, i.e., green wave. When the queue is long (Figure 2A), the offset is usually negative, and it represents (relatively) the time needed to release the queue at the succeeding intersection so that the incoming vehicles traveling from the preceding intersection are not slowed down by the queue; When the queue is short (Figure 2B), the offset is usually positive, and it represents the journey time of the vehicles traveling from the preceding intersection to the succeeding intersection. When the residual is high (Figure 2A), where demand exceeds available capacity, the green time is extended to allow more vehicles to be released, effectively increasing the cycle length; when the residual is low (Figure 2B), the green time remains unchanged.

    The cameras also provide the occupancy of the vehicles on the road. Occupancy in this context means the number of moving vehicles detected on each lane of the road. When the occupancy reading is constantly high (Figure 3A), a high volume of vehicles is being released, thus the green time is fully utilized; when the occupancy reading is low (Figure 3B), the queue has been completely discharged, and the green time is being under-utilized from this point onwards. SASCOO algorithm measures the duration for which the occupancy is low and decides to either reduce the green time for that phase, while effectively reducing its cycle length, or transfer it to other phases that need it.

    Problem Statement:
    Fixed time and VA signals that use in-ground loop detectors are unable to provide smooth traffic progression for vehicles traveling through a series of intersections.

    Summary of the Invention:
    A method of coordinated traffic signal control across multiple intersections

    Key Features of the Invention:

    1. A method of coordinated traffic signal control across multiple intersections.
    2. A system comprised of cameras coupled to a deep learning model to detect, locate and classify the vehicles.
    3. Each detected vehicle is assigned a unique identifier for tracking purposes.
    4. An automatic license plate recognition system to calculate the journey time, waiting time, and delays of the vehicles.
    5. An adaptive traffic signal system to process the quantity, location, and movements of the vehicles, i.e., queue, residual, occupancy, and journey time, in real-time to generate new coordinated signal timing plans that alter the offset, split, and cycle length across all connected intersections.
    6. A method of producing green wave progression along an arterial road across a series of intersections.
    7. Information such as, but not limited to, residual, queue, occupancy, journey time, waiting time, origin-destination, classification, PCU, and license plate are stored in the database.

    Patent Search:

    1. US8050854B1 – Chandra et al. – Sep. 24, 2008 Adaptive Control Systems and Methods
    2. US8103436B1 – Chandra et al. – Sep. 24, 2008 External Adaptive Control Systems
    3. US10490066B2 – Green et al. – Dec. 29, 2016 Dynamic Traffic Control
    4. US11100336B2 – Malkes et al. – Aug. 8, 2018 System and Method of Adaptive Traffic Management at an Intersection
    5. US10373489B2 – Malkes et al. – Jul. 9, 2018 System and Method of Adaptive Controlling of Traffic Using Camera Data
    6. US10373489B2 – Price et al. – Aug. 8, 2018 System and Method of Adaptive Controlling of Traffic Using Zone Based Occupancy

    Featured Table

     

    Features Present Invention 1 2 3 4 5 6
    A method of coordinated traffic signal control across multiple intersections
    A system comprised of cameras coupled to a deep learning model to detect, locate and classify the vehicles exter-nal only exter-nal only exter-nal only exter-nal only
    Each detected vehicle is assigned a unique identifier for tracking purposes track-ing only
    An automatic license plate recognition system to calculate the journey time, waiting time, and delays of the vehicles
    An adaptive traffic signal system to process the quantity, location, and movements of the vehicles, i.e., queue, residual, occupancy, and journey time, in real-time to generate new coordinated signal timing plans that alter the offset, split, and cycle length across all connected intersections queue only vague-ly occu-pancy only
    A method of producing green wave progression along an arterial road across a series of intersections vague-ly
    Information such as, but not limited to, residual, queue, occupancy, journey time, waiting time, origin-destination, classification, PCU, and license plate are stored in the database

    SASCOO ADAPTIVE GREENWAVE

    SASCOO (Step Adaptive Split Cycle Offset Optimizer) is an AI system that enables the traffic junctions to continuously distribute green light time equitably for all traffic movement.

    SASCOO refers to an artificial intelligence software that was used as part of the AdvanCTi smart traffic management system implemented by LED Vision in Pasir Gudang and Ipoh.

    Here are some key points about SASCOO:

    • It is described as an “AI Traffic Optimizer” that is trained on historical traffic data.
    • It collects real-time data from sensors and cameras installed at traffic junctions.
    • Using the real-time data, it dynamically optimizes traffic light timing and phases to improve traffic flow.
    • It implements adaptive signal control algorithms to adjust split times, cycle lengths, etc.
    • This optimization by SASCOO reduced congestion and improved traffic efficiency in Pasir
    • Gudang and Ipoh during the proof of concept projects.
    • The architecture diagram shows SASCOO as a core software component of the AdvanCTi platform.
    • SASCOO optimization developed in-house. SASCOO has been submitted and patent pending by LED Vision Sdn Bhd on 8 April 2022 with application number PI2022002279 (MyIPO)