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Smart Traffic Camera Market Size, Share Report and Trends 2035 Smart Traffic Camera Market is predicted to reach USD 67.18 Billion at a CAGR of 15.10% by 2035, Global Smart Traffic Camera Industry Growth by Camera Type, Application, Deployment Type, Region

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JPJ uses high-spec drones to monitor road traffic offences MACHANG: The Road Transport Department (JPJ) will use high-specification drones to monitor the travel of road users in Kelantan in conjunction with Ops Aidilfitri this year. JPJ Director-General Datuk Aedy Fadly Ramli said the use of drones was aimed at detecting road users who committed traffic offences, who could then be subject to action through Notice 114 (notice of summons for questioning). He said that for now, the use of high-specification drones is being implemented in Kelantan first before being expanded to other states. “We will use this drone starting March 13 to monitor the journey of the public back […]

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JSPT proposes installing dashcams in police cars BAGAN SERAI: The proposal to install dashboard cameras on every police car will be brought to the Inspector-General of Police in the near future to facilitate enforcement tasks in the field. Bukit Aman Traffic Investigation and Enforcement Department (JSPT) director Datuk Seri Muhammed Hasbullah Ali said the facility aims to enhance monitoring and enable the police to record and assess every incident that occurs in more detail. “This proposal is a good thing and makes it easier for us to track down the cause of accidents or other incidents involving road users.” “This method also helps the police to educate […]

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Skypark Airport Owners Discuss Development and Traffic Monitoring Plans Airport managers propose mechanisms for Dutch John and Manila airport development oversight.

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Open-source flow monitoring with SENSOR: Benefits and trade-offs - Help Net Security An open source flow monitoring platform delivers unsampled traffic analysis using interchangeable, standards-compliant tools.

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https://link.springer.com/article/10.1007/s10950-024-10267-8

https://link.springer.com/article/10.1007/s10950-024-10267-8

Figure 2: Frequency Analysis of Noise, Vehicle, and Earthquake Signals

Axes Explanation:
X-Axis (Frequency in Hz): Represents the frequency content of the seismic signals. Frequency (Hertz, Hz) refers to the number of oscillations per second.
Y-Axis (Amplitude, not explicitly labeled but inferred): Represents the strength or power of the seismic signal at different frequencies.

Color Representation:
Green: Noise signal components.
Blue: Vehicle-related seismic signals.
Red: Earthquake-related seismic signals.

Types of Lines (Dotted vs. Solid):
Each color has three dotted lines, corresponding to the East, North, and Vertical components of motion.
- East, North, and Vertical refer to the three axes of ground motion measured by a seismometer.
- Vertical component measures up-down movement.
- East and North components measure horizontal movements in their respective directions.

Interpretation & Relevance:
Noise (Green): Dominates at high frequencies (>30 Hz), which indicates environmental or anthropogenic disturbances.
Vehicle (Blue): Peaks between 5 Hz and 20 Hz, showing the frequency range of seismic signals generated by passing vehicles.
Earthquake (Red): Stronger in the lower frequency range (0-10 Hz), which is typical for seismic events as earthquake waves have lower frequencies and longer wavelengths.
Relevance to the Study: Helps in distinguishing between different seismic sources by analyzing their frequency characteristics.
Relevance to Real Life: Understanding frequency differences is crucial for earthquake detection, noise filtering, and distinguishing between natural and human-made seismic events.

Figure 2: Frequency Analysis of Noise, Vehicle, and Earthquake Signals Axes Explanation: X-Axis (Frequency in Hz): Represents the frequency content of the seismic signals. Frequency (Hertz, Hz) refers to the number of oscillations per second. Y-Axis (Amplitude, not explicitly labeled but inferred): Represents the strength or power of the seismic signal at different frequencies. Color Representation: Green: Noise signal components. Blue: Vehicle-related seismic signals. Red: Earthquake-related seismic signals. Types of Lines (Dotted vs. Solid): Each color has three dotted lines, corresponding to the East, North, and Vertical components of motion. - East, North, and Vertical refer to the three axes of ground motion measured by a seismometer. - Vertical component measures up-down movement. - East and North components measure horizontal movements in their respective directions. Interpretation & Relevance: Noise (Green): Dominates at high frequencies (>30 Hz), which indicates environmental or anthropogenic disturbances. Vehicle (Blue): Peaks between 5 Hz and 20 Hz, showing the frequency range of seismic signals generated by passing vehicles. Earthquake (Red): Stronger in the lower frequency range (0-10 Hz), which is typical for seismic events as earthquake waves have lower frequencies and longer wavelengths. Relevance to the Study: Helps in distinguishing between different seismic sources by analyzing their frequency characteristics. Relevance to Real Life: Understanding frequency differences is crucial for earthquake detection, noise filtering, and distinguishing between natural and human-made seismic events.

Figure 6: Model Prediction for Noise, Earthquake, and Vehicle Seismic Signals Over Time

Axes Explanation:
X-Axis (Time in Minutes, 0–60 min): Represents an hour-long seismic recording.
Y-Axis (Seismic Signal & Model Prediction): Represents seismic activity in three orientations:
- East-West (Top Panel)
- North-South (Middle Panel)
- Vertical (Bottom Panel)

Color Representation:
Red (Earthquake): Indicates moments when the model predicts earthquake activity.
Blue (Vehicle): Shows periods when the model detects seismic signals from vehicles.
Green (Noise): Represents background noise detected by the model.
Black (Seismic Data): The actual recorded seismic signal.

Interpretation & Relevance:
The model successfully identifies different sources of seismic activity.
Noise (Green) is persistent and appears frequently in the vertical component.
Vehicles (Blue) appear intermittently in the North-South component, matching expected vehicle movement.
Earthquakes (Red) are rare and appear as spikes in the East-West component.
Relevance to the Study: Demonstrates the model's capability to classify seismic events accurately.
Relevance to Real Life: Helps in automatic seismic monitoring, reducing false alarms, and improving earthquake early warning systems.

Figure 6: Model Prediction for Noise, Earthquake, and Vehicle Seismic Signals Over Time Axes Explanation: X-Axis (Time in Minutes, 0–60 min): Represents an hour-long seismic recording. Y-Axis (Seismic Signal & Model Prediction): Represents seismic activity in three orientations: - East-West (Top Panel) - North-South (Middle Panel) - Vertical (Bottom Panel) Color Representation: Red (Earthquake): Indicates moments when the model predicts earthquake activity. Blue (Vehicle): Shows periods when the model detects seismic signals from vehicles. Green (Noise): Represents background noise detected by the model. Black (Seismic Data): The actual recorded seismic signal. Interpretation & Relevance: The model successfully identifies different sources of seismic activity. Noise (Green) is persistent and appears frequently in the vertical component. Vehicles (Blue) appear intermittently in the North-South component, matching expected vehicle movement. Earthquakes (Red) are rare and appear as spikes in the East-West component. Relevance to the Study: Demonstrates the model's capability to classify seismic events accurately. Relevance to Real Life: Helps in automatic seismic monitoring, reducing false alarms, and improving earthquake early warning systems.

Figure 9: Impact of Time-Shifted Vehicle Noise on Earthquake Seismic Signals and Their Frequency Response

X and Y Axes
Left Side (Time-Domain Signal)
- X-axis: Time (in seconds) → Shows how the signal changes over time.
- Y-axis: Amplitude (measured in acceleration or velocity) → Represents the strength of the signal.
A strong earthquake will have a high-amplitude waveform, while weaker signals will have lower amplitudes.

Right Side (Frequency-Domain - FFT Representation)
- X-axis: Frequency (Hz) → Represents how often a certain vibration occurs per second.
- Y-axis: Amplitude (Intensity in frequency domain) → Shows how strong the signal is at different frequencies.

FFT helps separate different sources of vibrations:
- Low frequencies (~0-5 Hz): Typically associated with earthquakes.
- Higher frequencies (~10-20 Hz): More likely caused by vehicles or human activity.

Colors
Red Line: Represents the original earthquake signal.
Blue Line: Represents the vehicle signal (vibrations caused by a vehicle).
Black Line: Represents the combined signal (earthquake + vehicle noise).
By comparing these colors, researchers can determine how vehicle noise affects earthquake signal detection.

Type of Lines Used
Solid lines are used for all signals, but different colors distinguish earthquake signals, vehicle-induced noise, and their combination.
The presence of overlapping or diverging lines indicates interference between signals.

Explanation of Technical Words & Abbreviations
FFT (Fast Fourier Transform): A mathematical technique that converts a time-domain signal into a frequency-domain signal. It helps analyze the different sources contributing to the signal.

Why This Figure is Important (Scientific & Practical Relevance)
For Earthquake Studies: Helps understand how human activity (e.g., vehicle movement) interferes with seismic readings. This can improve earthquake detection and help seismologists filter out noise.
For Urban Planning.
For Public Safety.

Figure 9: Impact of Time-Shifted Vehicle Noise on Earthquake Seismic Signals and Their Frequency Response X and Y Axes Left Side (Time-Domain Signal) - X-axis: Time (in seconds) → Shows how the signal changes over time. - Y-axis: Amplitude (measured in acceleration or velocity) → Represents the strength of the signal. A strong earthquake will have a high-amplitude waveform, while weaker signals will have lower amplitudes. Right Side (Frequency-Domain - FFT Representation) - X-axis: Frequency (Hz) → Represents how often a certain vibration occurs per second. - Y-axis: Amplitude (Intensity in frequency domain) → Shows how strong the signal is at different frequencies. FFT helps separate different sources of vibrations: - Low frequencies (~0-5 Hz): Typically associated with earthquakes. - Higher frequencies (~10-20 Hz): More likely caused by vehicles or human activity. Colors Red Line: Represents the original earthquake signal. Blue Line: Represents the vehicle signal (vibrations caused by a vehicle). Black Line: Represents the combined signal (earthquake + vehicle noise). By comparing these colors, researchers can determine how vehicle noise affects earthquake signal detection. Type of Lines Used Solid lines are used for all signals, but different colors distinguish earthquake signals, vehicle-induced noise, and their combination. The presence of overlapping or diverging lines indicates interference between signals. Explanation of Technical Words & Abbreviations FFT (Fast Fourier Transform): A mathematical technique that converts a time-domain signal into a frequency-domain signal. It helps analyze the different sources contributing to the signal. Why This Figure is Important (Scientific & Practical Relevance) For Earthquake Studies: Helps understand how human activity (e.g., vehicle movement) interferes with seismic readings. This can improve earthquake detection and help seismologists filter out noise. For Urban Planning. For Public Safety.

Detecting earthquakes or just passing cars? 🌍🚗 A research uses deep learning to distinguish seismic signals from earthquakes, vehicles, and noise with 99% accuracy!📡🔬

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