Road Ice Risk Detection Using Distributed Sensor Networks
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Solution Overview
Problem
Current systems for detecting and warning drivers about ice on roads are not precise enough, as they rely on air temperature measurements, which are late and do not account for the actual road conditions, leading to inadequate anticipation and safety.
Innovation Solution
A system that uses geolocated information collection devices to measure pavement temperature and hygrometry, transmitting data via a wireless network to a remote server for real-time calculation of ice risk, providing drivers with accurate and timely information through portable applications and navigation systems.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If air temperature measurement is used for ice detection, then the system is simple to implement, but the measurement precision is insufficient and the warning is too late
Solution Approach 1:
The system segments the monitoring function by deploying multiple distributed collection devices along the road network, each equipped with temperature and hygrometry sensors. This segmentation enables localized precise measurements at multiple points, improving overall detection precision while maintaining individual device simplicity.
Solution Approach 2:
The system transitions from single-dimensional air temperature measurement to multi-dimensional monitoring by incorporating both temperature and hygrometry parameters, and later adding pavement temperature measurements. This dimensional expansion enables more accurate ice formation risk assessment.
2Measurement precision
If pavement temperature and hygrometry measurement is used, then the measurement precision is improved, but the device complexity increases
Solution Approach 1:
The collection devices are designed as universal multi-functional units that can measure both air temperature and hygrometry, and in some embodiments pavement temperature as well. This multi-functionality is achieved by integrating multiple sensor types into a single device platform, reducing overall system complexity despite enhanced measurement capabilities.
Solution Approach 2:
The system introduces an intermediary wireless communication network and central server that mediate between the distributed sensors and the user. This intermediary layer simplifies individual sensor devices by offloading data processing, storage, and analysis functions to the central infrastructure.
3Reliability
If fixed position sensors are used, then the measurement coverage is stable, but the energy consumption increases
Solution Approach 1:
The system implements periodic measurement and transmission cycles for fixed position sensors, rather than continuous operation. Sensors take measurements at intervals and transmit data periodically, significantly reducing energy consumption while maintaining reliable monitoring coverage throughout the road network.
Solution Approach 2:
Fixed position sensors are equipped with autonomous power management capabilities, including energy harvesting from environmental sources and intelligent sleep/wake cycles. This self-service approach enables sensors to operate independently for extended periods without external power intervention.
4Productivity
If onboard sensors with variable activation frequency are used, then the collection efficiency is optimized, but the device complexity increases
Solution Approach 1:
The system implements dynamic activation frequency for onboard sensors based on vehicle speed and environmental conditions. Sensors adjust their measurement and transmission frequency in real-time, increasing collection rate when vehicles are stationary or moving slowly, and reducing frequency at high speeds. This dynamic adaptation optimizes data collection efficiency while managing power consumption.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This system provides a real-time map of ice risk areas, optimizing route safety by combining data from both onboard and roadside sensors, minimizing bandwidth usage, and ensuring low maintenance with autonomous energy-powered devices.
Implementation Method 1
comprise a rechargeable electric battery (29) and a set of photovoltaic cells (27)
Data Source
Figure 1~3
Figure 4~8
Figure 5~6
AI summary
System for collecting and making available information concerning the risk of frost and/or the formation of black ice patches on the road network, the system comprising geolocated information collection devices (1,2) configured to measure soil temperature and ambient humidity and transmit this information remotely via a wireless network, a first part (E1) of the collection devices being installed on vehicles and a second part (E2) permanently installed at the roadside, a remote server (3) collecting the information and feeding into a database and calculating the risk of the formation of black ice patches on each segment of interest of the road network, and applications available on portable electronic devices (4) or on board vehicles (90-95),on which users can consult a map of black ice risks, or through which a navigation system can take this data into account to calculate an optimal and safe route.