Smart asphalt with predictive, diagnostic and Anti-icing capabilities

Abstract

The invention of smart asphalt with predictive, diagnostic, and anti-icing capabilities for improving safety and reducing accidents at urban intersections and intercity roads includes a network of sensors that collect data related to environmental conditions and road surface features. This data is then processed using AI algorithms to predict and detect the formation of black ice on the asphalt surface. Upon detecting or predicting the occurrence of black ice, a heating system embedded within the asphalt layers generates appropriate heat to prevent ice formation. Depending on the type and characteristics of each data, different AI algorithms are employed, and the accuracy of prediction and detection is improved using data fusion techniques. The system generates a real-time map of the location and extent of identified and predicted ice formation, enhancing the safety and maintenance of the road network.

Description

[0001] TITLE OF INVENTION

[0002] SMART ASPHALT WITH PREDICTIVE, DIAGNOSTIC, AND ANTI-ICING CAPABILITIES FOR IMPROVING SAFETY AND REDUCING ACCIDENTS AT URBAN INTERSECTIONS AND INTERCITY ROADS

[0003] TECHNICAL FIELD OF THE INVENTION

[0004] The present invention relates to systems and methods for detecting and preventing icing, specifically to a system for detecting and predicting icing in areas prone to such phenomena, such as intersections, bridges, sloped areas, and the like. It also pertains to the processing of data obtained from various sources and the application of artificial intelligence models to predict and detect icing events, as well as to send necessary warnings to facilitate appropriate actions based on the conditions. Additionally, the invention concerns smart asphalt, which includes measurement equipment, heating systems, a power supply system, and an automated control system designed to counteract the occurrence of icing based on the results of the data processing.

[0005] PRIOR ARTS

[0006] The main factors and parameters involved in road freezing include three key elements: road surface temperature, the presence of moisture (such as rain, snow, and fog), and the concentration of anti-icing agents like chlorides. Freezing specifically occurs due to the immediate freezing of rain on cold surfaces, especially at night or early morning, or from refreezing caused by a decrease in chloride levels after snowmelt. Accurately and continuously measuring these factors is challenging, as it is currently done mainly manually. This phenomenon poses a significant risk because it occurs suddenly and is difficult to predict using conventional methods, leaving little time for road managers and drivers to respond and take necessary actions, resulting in numerous traffic accidents annually. Therefore, in addition to precise detection of icing, it is essential to predict its occurrence for upcoming time intervals, so that necessary actions can be taken more accurately and quickly.

[0007] In cold climate areas, certain road zones, such as intersections, bridges, overpasses, sloped areas, regions not exposed to sunlight like shaded areas, and tunnels, are more prone to icing than other areas. Additionally, some regions with higher sensitivity and importance, such as airport runways and highways, require accurate prediction of icing before it occurs, so that appropriate actions can be taken. Therefore, the use of the present invention, especially for icing- prone areas like intersections and bridges, as well as for high-sensitivity areas such as airport runways, can be highly beneficial.

[0008] When rain, snow, or fog accumulates on the road surface and the asphalt temperature drops below freezing, the buildup of snow or water on the surface can lead to icing. The ice on the asphalt surface significantly reduces friction between the asphalt and the tires of passing vehicles, severely impacting driving and the performance of the braking system. Numerous statistics have shown that traffic accidents are significantly higher in snowy, rainy, and especially icy conditions compared to sunny weather.

[0009] When road icing occurs, deicing actions must be earned out quickly. One common method is the manual approach or the use of deicing and snow removal machinery. This method requires significant human labor and equipment. It is also very time-consuming and costly, making it unsuitable for large-scale applications. Another approach to combat icing is the use of chemical methods, where large amounts of salt, as an anti-icing agent, are spread over the asphalt surface. This method is widely used due to its effectiveness and simplicity. However, the distribution of large amounts of deicing agents on the asphalt surface can have numerous harmful effects on the environment and pose a threat to human health and the entire ecosystem. Additionally, after the ice melts, the concentration of deicing agents decreases, raising the freezing point and making the road surface prone to icing again. Some deicing materials, such as salt, can also cause corrosion, which negatively impacts the lifespan of infrastructure like bridges.

[0010] Therefore, the use of traditional methods is not recommended due to their destructive effects, the time-consuming nature of the process, and the high costs involved. Another method for combating icing is the use of electrical heating technology. For example, by placing heat generators within the road structure, this method prevents the formation of ice or, in the event of icing, helps melt the ice. The advantages of this approach include high safety, lower long-term costs, high effectiveness and efficiency, and no harmful environmental effects. Additionally, with proper design and implementation, this method can maintain the structural integrity of the road.

[0011] In the method using electrical heating technology to generate heat, the inability to predict icing events means that the heating system is only activated once the icing is detected. However, since melting the ice takes time, there is still a risk of accidents occurring. Additionally, in some cases, the heating system is kept active for extended periods during cold hours of the day. While this prevents icing, it results in very low energy efficiency. To address these issues, the present invention introduces a smart asphalt structure that includes various sensors for real-time data collection and an electrical heating system to prevent icing. This system is capable of predicting icing events for future time intervals, and therefore, not only prevents icing but also minimizes energy consumption. The design of the asphalt layers has also been optimized to improve the effectiveness of the electrical heating system.

[0012] Smart asphalt, an innovative integration of traditional asphalt with embedded sensor technology, represents a significant advancement in infrastructure management. This approach is designed to monitor road conditions in real time, providing vital data on factors such as temperature, humidity, and structural integrity. One of the most important and critical applications of smart asphalt is in detecting icing, where sensors can alert drivers and transportation authorities to hazardous conditions that are often invisible to the naked eye. Additionally, when icing is detected or predicted, various methods can be employed to address the phenomenon, including the use of deicing materials, deicing machinery, snow removal equipment, or electrical heating systems.

[0013] The benefits of smart asphalt go beyond safety. By facilitating timely repairs and maintenance, smart asphalt can extend the lifespan of roads and reduce overall infrastructure costs. Furthermore, the data collected from these sensors can improve urban planning strategies and traffic management, leading to optimized traffic flow and reduced congestion. As cities around the world seek to enhance the resilience and sustainability of their infrastructure, smart asphalt has emerged as a promising solution that combines safety, efficiency, and environmental awareness, making it an exciting area for study and application. Given these advantages, numerous studies and inventions related to smart asphalt have been presented in recent years. The following discusses some of the most important registered inventions in this field, with a focus on the applications of smart asphalt for the automatic detection and prevention of icing.

[0014] A US invention with publication No. US20230169856A1 Which was filed on 13 / 05 / 2021 titled “Apparatus and System for Detecting Road Surface Condition and Method for Detecting Road Surface Condition by Using Same” relates to an apparatus and system for detecting a road surface condition, wherein the road surface condition is determined through a sound signal; and a method for detecting a road surface condition by using same. The apparatus for detecting a road surface condition according to the present invention comprises: a sensor unit which is installed on a road and measures a sound signal generated according to a moving of a moving object on the road; and a control unit which distinguishes the sound signal measured by the sensor unit into normality or abnormality and determines, in case of the abnormality, the road surface condition including at least one of rainfall (wet), frozenness (icy), slush, and snow cover (snowy) so that a quick and accurate action corresponding to the road surface condition of a specific section can be made from a distanced place. A US invention with publication No. US20240183117A1 which was filed on 13 / 02 / 2024 titled “Device and method for estimating and managing road surface types using sound signals” introduced an electronic device for classifying road surface conditions using acoustic signals and a method for road surface classification. Additionally, a system and method for managing road surfaces through classification are provided. The road surface classification is performed using a multi-dimensional artificial neural network. The multi-dimensional artificial neural network functions as a classifier based on various information by incorporating at least one of the following data: image data, atmospheric data, or road surface temperature data, in addition to the input data related to the acoustic signal. As a result, more accurate road surface classification can be achieved by utilizing information obtained from multiple sources and processing it accordingly.

[0015] A US invention with publication No. US20230102248A1 which was filed on 15 / 12 / 2021 titled “System for detecting black ice on roads using beam forming array radar” a frost detection system, specifically a system for detecting road icing, is introduced. This system is capable of utilizing a reflector and beamforming array radar installed along the road to measure changes in conductivity based on the phase transition between water and ice on the road. Upon detection, the system can issue a warning and take appropriate action regarding the icy conditions.

[0016] A Korean invention with patent No. KR102431234B1 which was granted on 11 / 08 / 2022 titled “A black ice detection system using seismic waves” provided a system for frost detection using seismic waves. According to this invention, a seismic wave generator is installed on the road surface, and a seismic wave detection sensor is provided. The frost detection system is capable of identifying and analyzing seismic waves generated by frozen water present on top of the seismic wave generator, allowing it to detect the formation of ice on the road. As mentioned, the system employs a seismic wave, a seismic wave detection sensor, and a processing unit to determine the presence of frost.

[0017] A Korean invention with patent No. KR102312714B1 which was granted on 14 / 10 / 2021 titled ” SMART ROAD CONDITION ALARM SYSTEM USING Multi-sensor for determining road conditions and road condition judgment method” a system is presented that includes multiple sensors installed on a road, comprising one or more temperature and humidity sensors. A control unit is employed to determine and predict whether frost will occur based on the measured values. A communication unit is used to receive the results determined and predicted by the control unit. Additionally, a solar panel is used to power the sensors.

[0018] A Korean invention with patent No. KR102330612B1 which was granted on 24 / 11 / 2021 titled " Prediction apparatus of black ice and blow up in road surface” provided a system to accurately predict frost formation on road surfaces during winter and the blow-up phenomenon that occurs during a heatwave, as well as to notify the driver of impending frost or the blow-up event. The device for predicting black ice and blow-up events includes: a thermal imaging camera installed on one side of the road to measure the road surface temperature, temperature and humidity sensors, a control unit to predict black ice and blow-up events based on the road surface temperature measured by the thermal imaging camera and the atmospheric temperature and humidity measured by the sensors, and a system to report the prediction results to the traffic control center. Additionally, the invention utilizes a server for monitoring road conditions in the traffic control center.

[0019] A Korean invention with patent No. KR102643863B1 which was granted on 07 / 03 / 2024 titled “Black ice alarm system using multiple array sensor and deep learning” a system for road surface frost warning is provided, which employs a multi-sensor array and deep learning algorithms to process the collected data. The sensors include an infrared sensor, a temperature sensor, and a precipitation detection sensor. In this invention, by utilizing various sensors and deep learning algorithms, frost formation on the road surface is detected in winter within areas where frost is expected to occur. If frost is detected, an alarm will be triggered to prevent traffic accidents.

[0020] A Korean invention with patent No. KR102265311B1 which was granted on 14 / 06 / 2021 titled “Automatic detection type road freezing section notification system” a road freezing notification system is provided that detects the occurrence of frost in areas where this phenomenon frequently occurs. This system alerts the driver about the onset of frost by using a laser to display a marker on the road surface at both the start and end points of the frozen section. To achieve this, the road freezing notification system is an automatic detection type and includes: a detection unit that measures temperature, humidity, and precipitation on the road; a control unit that determines whether the road is frozen based on the data collected by the measurement unit; and a display unit installed along the roadside to inform the driver of the occurrence of frost when the control unit detects freezing. The display unit works under the control of the controller and uses a laser display to indicate a linear marker on the road surface at the starting and ending points of the frozen section. The display units are installed at regular intervals along the road to project the laser.

[0021] A Korean invention with publication No. KR20230164945 A which was filed on 26 / 05 / 2022 titled “System for providing black ice information according to freezing of road surface, and method for the same” generated frost information based on the level of risk on the road using low-cost road surface temperature sensors, along with data on air temperature, relative humidity, and rainfall. This information is then transmitted to snowplows, drivers, and others to prevent road accidents caused by winter frost. This invention utilizes a system and method for providing frost-related information, which can be classified as safety information, and is made available to the vehicle driver. A US invention with publication No. US20240119551A1 which was filed on 11 / 04 / 2022 titled " System and method for making snow removal decision” considered all three factors of frost formation, including road surface temperature, the presence of moisture on the road surface (such as snowfall, rainfall, dew, fog, and meltwater from snowplowing operations), and the concentration of de-icing agents (such as chlorides) applied to prevent freezing. By accurately measuring these factors, the interactions between them are also taken into account, allowing for the prediction of when the road will freeze. Therefore, this invention enables precise decision-making regarding snow removal, the timing of snow plowing, and the amount of de-icing materials to be used. This allows the road management center, regardless of snow plowing experience, to make accurate and timely decisions about when to perform snow removal operations.

[0022] A Korean invention with publication No. KR20190105165A which was filed on 21 / 02 / 2018 titled “Road Weather Information Forecasting System” a system for predicting road weather information is presented, which can help prevent accidents by providing risk-related information using weather data and road surface conditions. This invention utilizes sensors such as airflow sensors, temperature sensors, and humidity sensors to gather road surface data. In the road weather prediction system, comprehensive analysis of weather data and road condition information is conducted, providing real-time road surface information to drivers, thereby preventing hazards related to adverse weather conditions.

[0023] A Chinese invention with publication No. CN115605648A which was filed on 13 / 05 / 2021 titled “Apparatus and system for detecting road surface condition and method for detecting road surface condition by using the same” a device and system for detecting road surface conditions is introduced, where the road surface status is determined using an acoustic signal. The road surface condition detection device in this invention includes a sensor unit installed on the road that measures the acoustic signal generated by the movement of an object on the road. It also utilizes a control unit that detects whether the measured acoustic signal from the sensor unit is normal or abnormal. In the case of anomalies, such as rainfall, freezing, mud, or snow, the road surface condition is identified. This approach enables rapid and accurate remote actions to be taken based on the identified conditions.

[0024] A Chinese invention with patent No. CN115413318B which was granted on 02 / 02 / 2024 titled “Sensor-equipped system and method for monitoring the health, condition and / or status of road surfaces and vehicle infrastructure” introduced a system for monitoring urban infrastructure pavements. This system includes pavement infrastructure, a geogrid equipped with a large number of sensors, such as temperature sensors, pavement moisture sensors, ambient humidity sensors, force sensors, bending sensors, strain gauges, accelerometers, inclinometers, inertial measurement units, a microcontroller for data acquisition and transmission, and a communication network that transfers data from the microcontroller to a computational network. The computational network is configured to use a multi-parameter algorithm that makes decisions regarding the pavement infrastructure condition based on signals from various sensors. A Chinese invention with publication No. CN116908303 A which was filed on 12 / 05 / 2023 titled “Method for detecting blocking degree of permeable concrete pavement based on dynamic elastic modulus” presented a method for detecting the degree of clogging in permeable concrete pavements using dynamic elastic modulus measurements. This method involves placing ultrasonic probes on both sides of the pavement to measure the ultrasonic wave velocity. The wave velocity is determined based on the distance and the time it takes for the wave to travel between the probes. These data are then used to calculate the dynamic elastic modulus of the concrete, and a relationship between the dynamic elastic modulus and the pavement porosity is established. By comparing the calculated porosity with the designed porosity, this method can classify the condition of the pavement: no clogging if the porosity is above 85%, slight clogging for porosities between 60% and 85%, and clogging if the porosity is below 60%. This systematic approach enables effective monitoring and maintenance of permeable concrete systems, ensuring optimal drainage performance.

[0025] A WIPO international invention with publication No. WO2023127089A1 which was filed on 28 / 12 / 2021 titled “Deterioration prediction device, deterioration prediction method, and recording medium” a system for predicting deterioration to assess the future structural integrity of infrastructure through the integration of multiple data sources has been designed. This system includes mechanisms for obtaining sensor history data and details about the substructure's ground layers. By analyzing these data, along with measuring ground displacement, the system predicts the deterioration status of the structure over time. The prediction model takes into account various factors, including environmental conditions and soil characteristics, and distinguishes between soft and hard layers to adjust the predictions accordingly. When applied to road infrastructure, the system evaluates deterioration indicators such as cracks, potholes, and surface anomalies, providing visual outputs that plot predicted deterioration levels at multiple points. This comprehensive system facilitates preventive maintenance strategies and enhances the longevity and safety of infrastructure. A Chinese invention with patent No. CN2839355Y which was granted on 22 / 1 / 2006 titled “Antifreezing and fog proof safety pavement” relates to an anti¬ freezing and anti-fog safety road surface. The invention is composed of a road surface layer and a heating layer, wherein the heating layer is positioned on the position of 10-15CM under the road surface layer, and the heating layer can use heating steam pipelines and can also use electric heating pipes. The invention is especially suitable for regional road surfaces, such as a bridge floor, an airport, a gradient road surface, and a steep curve road surface. When the condition is allowed, the utility model can also be arranged on the whole road surface of a freeway. The arrangement of the utility model can increase the expedited property and the safety of roads.

[0026] A Chinese invention with patent No. CN102677573 A which was granted on 22 / 06 / 2016 titled “Heating system for epoxy asphalt steel bridge deck pavement and pavement method” relates to a heating system for epoxy asphalt steel bridge deck pavement and a pavement method. The heating system can be used for controlling the operation temperature in the epoxy asphalt steel bridge deck pavement process, thereby shortening the curing time of epoxy asphalt, further greatly shortening the construction period, and reducing the maintenance time before the opening to traffic. Simultaneously, the invention provides a pavement method using the heating system for epoxy asphalt steel bridge deck pavement; and the pavement method can enable the epoxy asphalt steel bridge deck pavement to be constructed in winter and can also be adopted in summer when fast curing is needed.

[0027] A Chinese invention with patent No. CN105463953A which was granted on 04 / 07 / 2017 titled “Device and method for melting ice and snow for steel-concrete combined track beam by heating steel pipes” provides a device and method for melting ice and snow for a steel-concrete combined track beam by heating steel pipes. The device comprises skin effect heating components arranged in the concrete of the top surface of the steel-concrete combined track beam, and the skin effect heating components comprise a plurality of heating steel pipes and cables passing through the heating steel pipes; skin effect heating components are also arranged on connecting steel plates for connecting a guide surface and side surfaces of the steel -concrete combined track beam; and the cables are connected in series to form a loop or are refluxed by utilizing the heating steel pipes, and single-phase alternating current is supplied in the cables. The device provided by the invention can be used for quickly melting ice and snow on the traveling surface of the steel -concrete combined track beam. A Chinese invention with patent No. CN201634983U which was granted on 17 / 11 / 2010 titled “Snow-melting and deicing device for ramp of highway or bridge” provides a snow-melting and deicing device for a ramp of a highway or a bridge which is characterized in that a heat-conductive wire, a temperature control switch, a circuit breaker and a indicator light which are connected in serials between a battle line and a zero line of a power supply, wherein the heat- conductive wire is positioned in the interior of a heat-conductive pipe, the heat- conductive pipe is fixed on the position between the road surface of the ramp of the highway or the bridge and the roadbed thereof by a pipe clamp, the external surface of the heat-conductive pipe is contacted with the temperature sensing contact of the temperature switch, when beginning to snow, the snow-melting deicing device is connected with the power supply by the circuit breaker, so that the heating wire is heated and transfers the heat to the pavement, the snow on the pavement cannot freeze so as to enable the vehicles to normally run, and the phenomenon that after the snow drops on the pavement, the work of snow-melting and deicing is carried out to cause the traffic jam can be avoided.

[0028] A Chinese invention with patent No. CN201660822U which was granted on 01 / 12 / 2010 titled “Anti -freezing and anti-sliding concrete pavement slab containing phase-change energy-storage materials” relates to an anti-freezing and anti-sliding concrete pavement slab containing phase-change energy-storage materials, which comprises a main body concrete structure layer, a stainless steel hollow tube layer containing phase-change energy- storage materials, and an anti-sliding concrete surface layer, wherein the main body concrete structure layer is manufactured from common concrete pavement materials; the stainless steel hollow tube layer is 3-5 cm away from the surface of the pavement slab, the outside diameter of hollow tubes ranges from 4-6 cm, the stainless steel hollow tube layer is formed through injecting phase-change energy- storage materials into the stainless steel hollow tubes, one end of each stainless steel hollow tube is sealed while the other end thereof is open, and the phase-change energy- storage materials are injected through the open ends after the pavement construction; and the anti-sliding concrete surface layer is manufactured from cement-based materials with the anti-sliding function.

[0029] A Chinese invention with publication No. CN102174793A which was filed on 02 / 03 / 2011 titled “Intelligent temperature-control anti-freezing bridge deck” discloses an intelligent temperature-control anti-freezing bridge deck, wherein the bridge deck is paved with a thermal insulation layer; a lower layer of concrete is cast on the thermal insulation layer; the lower layer of concrete is paved with steel pipes; the steel pipes are paved with reinforcing steel bars and pre -buried with a bridge deck temperature sensor, and then an upper layer of concrete is cast; the steel pipes are provided with electric-heating wires; the two ends of each steel pipe are sleeved in a steel slot; and a temperature controller is arranged on connection wires of the electric-heating wires.

[0030] A Japanese invention with publication No. JP2002188109A which was filed on 22 / 12 / 2000 titled “Anti-freezing and snow melting system for the road” provides An anti-freezing and snow-melting system for a road that prevents freezing of a road surface and melts snow on the road surface, wherein a far- infrared electric heater member is embedded in a pavement of the road. A far- infrared radiating element is mixed with the paving material on the upper side of the far-infrared electric heater member, and a far-infrared irradiating device is disposed above a road surface, the far-infrared irradiating device includes far- infrared radiating means, Reflection means for reflecting far- infrared rays radiated from the far-infrared radiation means toward the road surface.

[0031] A Korean invention with publication No. KR20080066507A which was filed on 12 / 01 / 2007 titled “The road which equipped heat rail to be able to melt freezing prevention and a snow” a road equipped with hot-wires for freeze prevention is provided to prevent snow from piling on a road and melt frozen snow on the road by heating the hot-wires, which are buried under the ground and remote- controlled. In a road equipped with hot wires for freeze prevention, the hot wires are buried under an asphalt or a surface layer, being covered with hot-wire protection pipes. The hot wires are buried under a vehicle road and an aircraft away. For easy maintenance and protection of the hot wire, the hot wires are covered with the protection pipe. When it snows, the hot wires are heated by supplying power to a control center.

[0032] A Chinese invention with publication No. CN105788288A which was filed on 17 / 12 / 2014 titled “Intelligent system for monitoring icing on pavement and monitoring method thereof’ comprises a fisheye camera, a road icing detector, a signal controller, and a display terminal. The input ends of a roadbed temperature sensor, an air humidity sensor, a vibration sensor, and a pavement conductivity probe are respectively connected with the input end of a detection control circuit, and the output end of the detection control circuit is connected with an input end of the signal controller. The output end of the fisheye camera is connected to another input end of the signal controller, and the output end of the signal controller is wirelessly connected to the display terminal. The intelligent system prevents error detection according to the detection of pavement conductivity, roadbed temperature, air humidity, and vibration above the pavement in combination with image acquisition of the fisheye camera. Once the signal controller sends out pavement icing signals, workers can determine the pavement icing situation according to the image information received in the display terminal in combination with icing signals and timely take measures.

[0033] A Chinese invention with patent No. CN113257000A which was granted on 25 / 10 / 2022 titled “Intelligent detection early warning system and method for road black ice” discloses an intelligent detection and early warning system and method for black ice on a road, which comprises a front-end system and an Internet of things platform in signal connection with the front-end system, wherein the front-end system comprises: the main body structure comprises a base arranged on an anti-collision fence of a highway, a vertical rod vertically arranged on the base and an electric box, wherein the bottom of the electric box is communicated with the external environment; the power supply system comprises a solar panel arranged at the top end of the upright rod and a storage battery which is arranged in the electric box and is electrically connected with the solar panel; the sensor system comprises a plurality of redundant temperature sensors, a humidity sensor and a condensation ice sensor which are arranged in an electric box; the intelligent gunlock recognition system comprises an Al camera with edge computing capability and an RS-485 communication line; the sensor system and the intelligent bolt system identification system are electrically connected with the storage battery.

[0034] A Chinese invention with publication No. CN113917564A which was filed on 13 / 08 / 2021 titled “Multi-parameter analysis remote sensing type road surface meteorological condition detector and detection method” a multi-parameter analysis remote sensing type road surface meteorological condition detector is used for measuring road surface meteorological conditions and is characterized by comprising an instrument shell, a multi-beam laser spectrum analysis measuring component, an infrared radiation road surface temperature measuring component, a temperature and humidity measuring component and a microcontroller are arranged in the detector; a multi -parameter analysis and judgment algorithm module is arranged in the microcontroller; the multi-beam laser spectrum analysis measuring component, the infrared radiation road meter temperature component and the temperature and humidity measuring component are respectively connected with the microcontroller, and collected measuring data are sent out through an RS232 / 485 serial port communication module connected with the microcontroller after being calculated and analyzed by the microcontroller.

[0035] DESCRIPTION OF THE INVENTION The present invention introduces a system and method for predicting, diagnosing, and anti-icing on smart asphalt roads, specifically for intersections and other icing-prone areas, using various sensors and data processing with artificial intelligence.

[0036] In the upper layer of the smart asphalt, the invention utilizes additives with high thermal conductivity, such as metallic particles, which allow heat to be distributed more rapidly across the surface, enabling faster ice melting with lower energy consumption. Data collection sensors are also placed on this layer. Additionally, heating cables are uniformly embedded in the middle layer of the asphalt to generate heat. Beneath the heating cables, thermal insulating materials are used to prevent heat transfer to the lower layers, ensuring that the generated heat is effectively directed to the upper layer. The activation and deactivation of the heating system are controlled by a dedicated control system, based on the real-time data processing results.

[0037] One of the objectives of the present invention is to predict the time and location of icing events on smart asphalt. The smart asphalt in this invention can be made from either conventional asphalt or porous asphalt. Predicting the time and location of icing on asphalt can offer numerous advantages. For example, by activating the embedded heating system at the right time, icing can be prevented, traffic management can be optimized, deicing materials can be distributed and sprayed in smaller amounts but with greater precision and accuracy at specific locations, and instructions and warnings can be sent to drivers more quickly and accurately for the use of specialized equipment. Given the various factors influencing asphalt icing, such as temperature, humidity, the amount of deicing agents used, and others, predicting the time and location of icing with high accuracy is a difficult and challenging task.

[0038] Many variables can influence the prediction of icing events, including historical data, information regarding the type of asphalt and materials used in it, weather forecasts, and real-time data measured from the asphalt. The real-time data is obtained based on the information gathered from sensors embedded on the surface or various layers of the smart asphalt. Additionally, real-time information will also be collected from other sensors placed in the environment. This real-time data includes sensors for surface and layer temperatures of the asphalt, asphalt moisture sensors, the level of water or snow accumulation on the asphalt surface, freezing temperature, the amount and concentration of deicing agents applied on the asphalt surface, and environmental data such as ambient temperature, humidity, and wind speed. Additionally, for each sensor or array of sensors placed together, a positioning module, such as a Global Positioning System (GPS), will be used. Furthermore, for each sensor or sensor array, location-specific information such as road slope, surrounding vegetation, and other factors will be uniquely determined and considered in the processing. The sensors placed on the asphalt can be installed at specific intervals, depending on the type of road and the climate of the area. Moreover, in critical areas or regions with a higher likelihood of icing, it is necessary to place additional sensors to enhance the safety, accuracy, and reliability of icing prediction and detection.

[0039] The signals related to real-time data received may exhibit very different behaviors. For example, temperature data is a time-dependent signal, with changes occurring smoothly and continuously over time. However, the signal related to the concentration of deicing agents used is a static signal, which does not change continuously and only shows significant variations at specific times or under certain conditions. In this invention, depending on the type of real-time signal received, different artificial intelligence models will be used for processing and predicting icing. Using the appropriate Al model for each type of signal will lead to a significant improvement in the accuracy of icing prediction.

[0040] Figure 1 shows the different components used in the present invention. As illustrated, the invention comprises two main sections: the environmental data collection and heating unit, and the central processing unit. The environmental data collection unit gathers real-time information from the environment and the asphalt, such as temperature and humidity, and continuously transfers it to the central processing unit. Based on the results of the processing, this unit also controls the activation and deactivation of the asphalt heating system to prevent icing. The central processing unit uses the received real-time data, along with other data such as weather forecasts and historical data, to predict and detect icing events. The results of the processing, along with any necessary warnings, are then transmitted to relevant personnel and departments. Additionally, these results are used to control the asphalt heating system automatically and intelligently.

[0041] Figure 2a illustrates an example of how the data collection sensors are positioned on the asphalt according to the present invention. In addition to the sensors monitoring the condition of the asphalt, environmental sensors are also used to gather data from the surrounding environment. These two categories of sensors are responsible for collecting real-time information. The real-time data includes surface and layer temperature sensors, asphalt moisture sensors, the level of water or snow accumulated on the asphalt surface, freezing temperature, the amount and concentration of deicing agents applied on the asphalt, as well as environmental data such as ambient temperature, humidity, and wind speed. Additionally, for each sensor or array of sensors placed together, a positioning module, such as a Global Positioning System (GPS), will be used.

[0042] To transmit the data collected from the sensors installed on the asphalt and in the surrounding environment to the central processing unit, a data transmission unit is used. For this purpose, each sensor or sensor array located at a specific position transmits data to a local gateway using data transfer protocols such as Zigbee, Bluetooth Low Energy (BLE), Long Range Wide Area Network (LoRaWAN), and Message Queuing Telemetry Transport (MQTT). The data is then collected via the gateway and transmitted to the central processing unit through a high-bandwidth connection such as a 4G / 5G networks, satellite, or Ethernet. In this invention, the LoRaWAN protocol is used due to its long range and low energy consumption. To power the environmental sensors, batteries, solar panels, and in some cases, direct connection to the municipal power grid are used. For the sensors embedded in the asphalt, there are more limited options for power supply due to environmental constraints. For this category of sensors, energy harvesting techniques have been used to collect energy from the surrounding environment. Piezoelectric sensors are employed for this purpose, as they generate electricity from mechanical stress and convert the pressure exerted by vehicles moving over the sensors into usable electrical power for the embedded sensors. Additionally, in some embodiments and implementations of the present invention, power is supplied through a direct connection of the sensors via a connecting cable to a nearby power generation source placed along the road. This roadside power source can be of various types, such as solar panels or the municipal electrical grid.

[0043] Figure 2b shows another visualization of how the environmental and surface sensors, as well as the display designed to show warnings to drivers at an intersection, are positioned. As mentioned, in areas like intersections and junctions where vehicles make brief stops, the heat generated by the vehicle causes snow to melt. However, when the temperature is low or drops suddenly, the moisture can quickly freeze, leading to the formation of ice. In environments such as intersections and bridges, where the likelihood and frequency of icing events are higher, the use of an embedded electrical heating system in the asphalt layers is crucial. Figure 2c illustrates the electrical heating system and its placement in the asphalt layers. Additionally, to power the electrical heating system and other equipment, solar cells along with a storage battery system with appropriate capacity are used. Moreover, in situations where the electrical heating system requires high power, the use of the national power grid to supply the necessary power is also possible. Figure 2c shows a view of the smart asphalt layers used in the present invention, along with the heating system and data collection sensors. The smart asphalt used in this invention can be made from various types of asphalt for different applications, such as conventional asphalt or porous asphalt. As illustrated in the figure, the smart asphalt generally consists of three layers: the Upper Layer, the Binder Layer (or middle layer), and the Base Layer. The materials used in each layer may vary based on factors such as the type of asphalt, its intended use, and the surrounding environment.

[0044] Based on an embodiment of the present invention, in the Upper Layer, which is the topmost layer of the asphalt and is directly exposed to traffic and weather conditions, asphalt data collection sensors are embedded. In this invention, to combat freezing using the embedded electric heating system, it is necessary to enhance the thermal conductivity effectiveness in the Upper Layer by incorporating materials with high heat transfer properties in the composition of the top asphalt layer. For this purpose, various materials such as metal particles, carbon nanotubes, and graphite can be used. In the present invention, waste iron particles have been utilized due to their remarkable performance in improving heat transfer. The use of waste iron particles ensures better and faster heat distribution and transfer. Additionally, data collection sensors for the asphalt are also integrated into this layer.

[0045] The Binder Layer, or middle layer, serves to connect the Upper Layer to the Base Layer and provides structural support and load distribution. In the present invention, an electric heating system is used in this layer, which is placed uniformly and in a spiral pattern as shown in Figure 2c. For this purpose, heating cables are used, and materials such as nickel-chromium alloy, carbon fiber heating wire wrapped with silicon rubber, and carbon fiber heating wire wrapped with Teflon can be employed. At the bottom of the heating system, to prevent energy loss and enhance the effectiveness of freezing prevention, materials with thermal insulation properties are used. For this, aluminum silicate ceramic fiber powder is employed as a thermal insulator to prevent the reduction of stability between layers and to stop energy from transferring to the Base Layer, thereby preventing its loss. The use of this insulating material, combined with the high thermal conductivity materials used in the Upper Layer, allows for faster freezing prevention and effectively reduces energy waste.

[0046] In Figure 3, temperature data collected at different times using the sensor placed on the surface of the asphalt according to the present invention is shown. As shown, the temperature data exhibits continuous and slow variations, without significant changes in a short period of time. Additionally, in Figure 4, data regarding the percentage of Saline Concentration at different times, collected from the sensor placed on the asphalt surface according to the present invention, is shown. As can be seen, this data exhibits rapid and pulse-like fluctuations, with a sharp increase occurring at the time of salt application. As mentioned earlier, in the present invention, based on the type of data received and the characteristics of the corresponding signal, different artificial intelligence models will be used. This approach improves the accuracy of freeze prediction, allowing for the necessary actions to be taken based on the prediction. For instance, if freezing is predicted to occur in a specific area, the electric heating system can be activated promptly, preventing incidents and hazards associated with freezing.

[0047] In Figure 5, the stages of processing various types of collected data for detecting and forecasting the occurrence of freezing according to the present invention are shown. As illustrated, the invention utilizes different types of data to predict the time of freezing. The data used includes historical data, meteorological data, and real-time data collected from the environment. Initially, based on the type of data and its characteristics, the Feature Extraction step is performed, in which useful features are extracted from each data source. Next, in the Data Concatenation stage, the extracted features from the input data are combined and prepared for input into the trained artificial intelligence model for Data Fusion, which is used to forecast the occurrence of freezing. Finally, the output will provide the remaining time until the freezing event occurs.

[0048] Historical data is crucial for predicting freezing events as it provides insights into past incidents and patterns related to the formation of this phenomenon. By analyzing historical records of temperature, precipitation, and road conditions, machine learning models can identify trends and correlations that indicate potential future freezing events. This data can reveal the frequency and severity of freezing occurrences under specific meteorological conditions, allowing the model to learn from previous patterns. The integration of historical data helps establish a baseline for predictions and improves the reliability and accuracy of the model over time. The historical data used includes meteorological information, environmental data, freezing events (or lack thereof), and the time of occurrence, categorized for each region or point of interest for detecting and predicting freezing.

[0049] Meteorological data, including temperature, humidity, wind speed, and precipitation, play a crucial role in predicting freezing events. By using realtime weather data, as well as weather forecasts for upcoming periods, models can assess conditions that contribute to the formation of ice, such as a sudden temperature drop or precipitation during cold weather. For example, understanding how specific combinations of temperature and humidity levels lead to the formation of black ice enables more accurate predictions. Additionally, predictive models that integrate weather data can quickly adapt to rapidly changing weather conditions, enhancing their responsiveness and accuracy in forecasting potential freezing events. Meteorological data is collected from the nearest weather station to the area of interest for freezing detection and is processed accordingly.

[0050] The combination of historical, meteorological, and real-time environmental data creates a comprehensive dataset that significantly enhances the accuracy of freeze predictions. This multifaceted approach enables machine learning algorithms to learn from a broader range of data, leading to more precise predictions. The synergy between these datasets allows for more complex modeling, such as ensemble learning, which can improve prediction accuracy by aggregating outputs from different models. Moreover, the integration of diverse data sources facilitates the identification of complex interactions between variables that might not be apparent when analyzing each dataset individually. This holistic perspective can lead to earlier and more accurate freeze warnings, ultimately improving road safety and enabling better resource allocation for road maintenance and response teams. By leveraging the strengths of each type of data, the prediction system becomes more robust, adaptable, and effective in mitigating the risks associated with ice formation.

[0051] In addition, as shown in Figure 5, the present invention uses AI models with different structures to analyze the real-time data collected. The selection of the AI structure and model for sensor data analysis is based on the type and characteristics of the data. To this end, the real-time data collected from the environment is categorized into two groups: data with slow changes and data with rapid changes. In the present invention, environmental and asphalt temperature, humidity of the environment and asphalt, and the amount of water and snow on the asphalt surface are categorized as data with slow changes. Meanwhile, real-time data related to freezing temperature, concentration of de-icing materials, type of material, and wind speed are categorized as data with rapid changes.

[0052] For real-time data with slow changes, various types of time-series neural networks, such as Recurrent Neural Networks (RNN), Long Short-Term Memory (LSTM), Gated Recurrent Units (GRU), and other similar networks, can be used. In the present invention, as shown in Figure 5, LSTM networks are utilized, where the relevant data types for the desired time window are input into the network. Figure 6 illustrates the structure of an LSTM cell used in the present invention, which includes a forget gate, input gate, output gate, and memory cell. For processing real-time data with rapid changes, a Multilayer Perceptron (MLP) is employed. Using fully connected layers, this deep neural network is capable of extracting relevant features for predicting freezing events. The extracted features from both the LSTM and MLP networks, along with features related to historical and meteorological data, are then concatenated using the Data Concatenation layer before entering the Data Fusion section. In the Data Fusion section, various methods, such as Majority Voting, Weighted Averaging, Ensemble Methods, etc., can be used. In the present invention, deep learning-based Data Fusion techniques are specifically utilized. The use of Data Fusion ensures that the generated predictions have higher accuracy and reliability.

[0053] The final output, as shown in Figure 5, is the remaining time until a freezing event occurs on the asphalt. This output can belong to one of the classes, which include: no likelihood of freezing, freezing occurring within the next 5 minutes, freezing occurring within the next 10 minutes, freezing occurring within the next 20 minutes, freezing occurring within the next 40 minutes, freezing occurring within the next 1 hour, freezing occurring within the next 2 hours, freezing occurring within the next 4 hours, freezing occurring within the next 10 hours, and other future time intervals. Additionally, the probability of each of these classes will be expressed as a numerical value between zero and one, where a value closer to one indicates a higher likelihood of freezing occurring within the predicted time frame. Given the ability to predict freezing events at various time intervals, necessary actions such as activating the electric heating system can be taken in advance, and relevant warnings can be sent to predefined individuals and organizations.

[0054] To train the artificial intelligence models used in the present invention, training data was collected, which included real-time data obtained from environmental and asphalt sensors, weather forecast data, and historical data for various regions. These data were gathered and classified from different areas at various times of day. Additionally, data was collected from different types of asphalt, such as regular asphalt, porous asphalt, and asphalt with various materials and additives, to improve the accuracy and generalizability of the Al models for different conditions. Ultimately, using the collected data, the AI models were trained, evaluated, and tested for performance. Furthermore, over time, all data and results from the system introduced in the present invention will be collected and used to retrain the models in order to continuously improve their accuracy. In Figure 7, the flowchart for processing asphalt surface data to detect the occurrence of ice formation, trigger warnings, and activate the electric heating system if necessary, according to the present invention, is shown. As depicted, the data collected from the asphalt surface is analyzed to detect the presence of ice. Ice formation occurs when moisture is present on the asphalt and the asphalt temperature is lower than the freezing point. If these conditions are met, it indicates the occurrence of ice. In the event of ice formation, necessary alerts will be sent to predefined individuals and organizations, and the electric heating system will be activated to remove the ice in the affected area. If the conditions for ice formation are not met, the system will activate the ice prediction process for future time periods, as shown in Figure 8.

[0055] In Figure 8, the flowchart for processing various types of data to predict the occurrence of ice formation and send necessary warnings to prevent it, according to the present invention, is shown. In the absence of ice formation, as examined in Figure 6, the data is processed for forecasting the ice phenomenon. If necessary, the results and warnings related to the ice prediction, along with the time and location of the predicted event, are sent to the relevant individuals and organizations. Based on the output results of the ice prediction and detection, the necessary signals to activate or deactivate the electric heating system at the designated location are sent. In this way, before ice formation occurs, proactive and intelligent control of the electric heating system ensures that the necessary actions are taken to prevent it, thereby mitigating the harmful effects of this phenomenon.

[0056] Additionally, these warnings regarding the detection and prediction of ice formation are sent to pre-designated individuals and organizations, based on the level of risk and location of the event. These notifications are typically sent to local transportation authorities and highway maintenance organizations, who are responsible for road safety. They can take immediate actions to reduce risks, such as deploying salt trucks (if the electric heating system is not in use in the affected area) or adjusting traffic warning signs, and modifying driving regulations. Furthermore, as shown in Figure 2b, based on the level of risk and the location of predicted or detected ice formation, drivers are also alerted via road signs or warning boards. The warning information includes vital data such as the exact location of the detected or predicted ice, the current weather conditions (temperature, humidity, and precipitation), and the anticipated duration of the icy conditions. This information not only aids in immediate decision -making but also assists in planning future preventive measures.

[0057] Generally, the present invention comprises at least 3 layers of asphalt, at least one sensor for collecting temperature, humidity, water or snow accumulation height and freezing temperature, at least one electric heating system, at least one heat-generating cable, at least one positioning system (GPS), at least one central processing unit, at least one artificial intelligence module for data processing, at least one artificial intelligence algorithm, at least one data collection unit, at least one data transmission system, at least one power source including solar panels, batteries, or the city power grid, and at least one warning system, and at least one piezoelectric sensor. The thermal conductive materials in the upper layer are selected from materials such as metal particles, carbon nanotubes, and graphite, specifically using recycled iron particles. Also, the electric heating system uses uniformly spiraled heating cables made of nickel-chromium alloy, carbon fiber heating wire wrapped with silicon rubber, and carbon fiber heating wire wrapped with Teflon.

[0058] The use of thermal insulating materials, including aluminum silicate ceramic fiber powder, is employed to prevent energy transfer to the lower asphalt layers and improve heating performance. The data-collecting sensors are connected to a local gateway using communication technologies such as LoRaWAN or Zigbee. Also, environmental data from environmental sensors, including temperature, humidity, and wind speed, is sent to the central processing unit. The meteorological data is sent to the system and, after feature extraction, is combined with data collected from the asphalt to provide an accurate prediction of freezing. Additionally, real-time data is processed using appropriate Al models to predict freezing. The collected data from sensors is categorized and processed based on the type of data, such as signals with gradual or sharp changes.

[0059] In this invention, freezing predictions automatically activate or deactivate the electric heating system. The Long Short-Term Memory (LSTM) neural networks are used to process real-time data with gradual changes, and Multi-Layer Perceptron (MLP) is used to process real-time data with sharp changes. Al models and deep learning techniques integrate historical, meteorological, and real-time data to predict freezing. Also, the system predicts the freezing time within different time intervals, including 5 minutes, 10 minutes, 20 minutes, 40 minutes, 1 hour, 2 hours, 4 hours, and 10 hours. Training data, including data collected from various environments, is used to improve the accuracy of the AI models. The electric heating system is powered by energy sources such as solar panels and the city power grid. The system predictions are sent as alerts to drivers or pre-defined relevant authorities. Also, piezoelectric sensors are used to power embedded sensors in the asphalt. Furthermore, the data collection system from sensors is designed using wireless network technologies to reduce energy consumption and increase communication range. BRIEF DESCRIPTION OF THE FIGURES

[0060] Figure 1 shows the different components used and how they are interconnected according to the present invention.

[0061] Figure 2a shows an example of how the data collection sensors are placed on the asphalt according to the present invention.

[0062] Figure 2b shows a view of an intersection and the placement of asphalt and environmental data collection sensors, as well as the warning notification in the environment according to the present invention, including:

[0063] 1. Sensors placed on the asphalt surface

[0064] 2. Solar cells and energy storage unit

[0065] 3. Status display and environmental sensors

[0066] Figure 2c shows a view of the smart asphalt layers used in the present invention, along with the heating system and data collection sensors, including:

[0067] 1. Upper layer

[0068] 2. Binder layer and Heating cables

[0069] 3. Base layer

[0070] 4. Sensors

[0071] Figure 3 shows the temperature data collected at different times using sensors placed on the asphalt surface according to the present invention.

[0072] Figure 4 shows the data related to the percentage of saline concentration at different times using sensors placed on the asphalt surface according to the present invention.

[0073] Figure 5 shows the stages of processing various collected data to forecast the time of ice formation according to the present invention.

[0074] Figure 6 shows one of the LSTM cells used for processing data to forecast the time of ice formation according to the present invention, including:

[0075] 1. Input gate

[0076] 2. Output gate

[0077] 3. Cell state 4. Forget gate

[0078] Figure 7 shows a flowchart of processing the asphalt surface data to detect ice formation, send warnings, and activate the electric heating system if necessary, according to the present invention.

[0079] Figure 8 shows a flowchart of processing various data to predict the time of ice formation and send necessary warnings to prevent ice formation according to the present invention.

Claims

What is claimed is:

1. A smart asphalt with predictive, diagnostic, and anti-icing capabilities for improving safety and reducing accidents at urban intersections and intercity roads, comprising at least 3 layers of asphalt, at least one sensor for collecting temperature, humidity, water or snow accumulation height and freezing temperature, at least one electric heating system, at least one heat-generating cable, at least one positioning system (GPS), at least one central processing unit, at least one artificial intelligence module for data processing, at least one artificial intelligence algorithm, at least one data collection unit, at least one data transmission system, at least one power source including solar panels, batteries, or the city power grid, and at least one warning system, and at least one piezoelectric sensor.

2. The smart asphalt according to claim 1, wherein the thermal conductive materials in the upper layer are selected from materials such as metal particles, carbon nanotubes, and graphite, specifically using recycled iron particles.

3. The smart asphalt according to claim 1, wherein the electric heating system uses uniformly spiraled heating cables made of nickel-chromium alloy, carbon fiber heating wire wrapped with silicon rubber, and carbon fiber heating wire wrapped with Teflon.

4. The smart asphalt according to claim 1, wherein the use of thermal insulating materials, including aluminum silicate ceramic fiber powder, is employed to prevent energy transfer to the lower asphalt layers and improve heating performance.

5. The smart asphalt according to claim 1, wherein data-collecting sensors are connected to a local gateway using communication technologies such as LoRaWAN or Zigbee.

6. The smart asphalt according to claim 1, wherein environmental data from environmental sensors, including temperature, humidity, and wind speed, is sent to the central processing unit.

7. The smart asphalt according to claim 1, wherein meteorological data is sent to the system and, after feature extraction, is combined with data collected from the asphalt to provide an accurate prediction of freezing.

8. The smart asphalt according to claim 1, wherein real-time data is processed using appropriate Al models to predict freezing.

9. The smart asphalt according to claim 1, wherein the collected data from sensors is categorized and processed based on the type of data, such as signals with gradual or sharp changes.

10. The smart asphalt according to claim 1, wherein freezing predictions automatically activate or deactivate the electric heating system.

11. The smart asphalt according to claim 1, wherein Long Short-Term Memory (LSTM) neural networks are used to process real-time data with gradual changes, and Multi-Layer Perceptron (MLP) is used to process real-time data with sharp changes.

12. The smart asphalt according to claim 1, wherein Al models and deep learning techniques integrate historical, meteorological, and real-time data to predict freezing.

13. The smart asphalt according to claim 1, wherein the system predicts the freezing time within different time intervals, including 5 minutes, 10 minutes, 20 minutes, 40 minutes, 1 hour, 2 hours, 4 hours, and 10 hours.

14. The smart asphalt according to claim 1, wherein training data, including data collected from various environments, is used to improve the accuracy of the AI models.

15. The smart asphalt according to claim 1, wherein the electric heating system is powered by energy sources such as solar panels and the city power grid.

16. The smart asphalt according to claim 1, wherein system predictions are sent as alerts to drivers or pre-defined relevant authorities.

17. The smart asphalt according to claim 1, wherein piezoelectric sensors are used to power embedded sensors in the asphalt.

18. The smart asphalt according to claim 1, wherein the data collection system from sensors is designed using wireless network technologies to reduce energy consumption and increase communication range.

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