IOT Data: Connected & Autonomous Vehicle, Making sense of data
Posted by Jai on January 19, 2017
In this post, we will explore the possibilities of connected & autonomous vehicle driving data availability, and making sense of this IOT data to deliver stack of services for all the parties involved like customers, manufacturers, governance bodies and dealers etc. and creating host of service for complete ecosystem.
The trend is in coming years by 2025-2030 all the vehicles will be connected to internet in one or other way. As per the report,
Scenario for value shifts in the auto industry, 2015–30
Estimated connected car revenues (and market share) by product package, 2015–22
One way or other using Embedded, tethered or integrated solution going to provide your vehicle connectivity with the different platforms. The rise of autonomous vehicle will take the connectivity to next level for seamless user experience.
Twenty-five Gigabytes per hour: That’s how much data a connected car will upload/process every hour. Connected cars will send 25 gigabytes of data to the cloud every hour
Not all the data necessarily need to move to cloud system, it is up to vehicle internal communication system to pass only relevant information to cloud which can be used for further analysis for providing different features.
Based on your connected vehicle solutions, variety of sensor data, driving data, location data and ecosystem data is retrieved from the vehicle.
Vehicles today have about 40 microprocessors and dozens of sensors that collect telematics and driver behaviour data, and that data can be analysed in real-time to keep the vehicle’s performance, efficiency, and safety in check.
IoT smart sensor and actuator
- Acceleration: Capture X/Y/Z g values.
- Electric: Capture electric/battery signals to vehicle start/stop. Capture headlight information.
- Levels: Capture Fuel, Fluid, liquid oil. Capture air pressure points.
- Motion: Capture velocity, proximity, image sensors data.
- Temperature: Capture temperature at different components of vehicle.
- Moisture: Capture inside/outside vehicle air moisture data.
- Sound: Capture vehicle vibration information data.
On-board diagnostics (OBD) refers to vehicle’s self-diagnostic and reporting capability.
- Battery Voltage
- engine temperature
Any faults with the vehicle engine or sensors is reported.
DTCs are alphanumeric codes that are emitted by the on-board diagnostic systems in the car, and they typically signal when a vehicle sensor reports values outside the normal or accepted range.
Proprietary PID information
Based on custom embedded firmware solutions or telematics control unit can allow access to vehicle proprietary information from different available sensors inside the vehicle.
- Odometer reading
- Air bag status
- Tyre pressure
- Door control status
- Infotainment system status
- Front/Rear headlights status
- Seat belt status
- Headlight levels
- Rain sensors
- Wiper usage
GPS chip combined together with telematics solution allows to gather navigational data for the vehicle.
Acceleration sensor sharing data on different axis allows build multiple features around same.
- X/Y/Z axis acceleration values
GSM information with embedded SIM allows to gather cell tower, signal strength information.
- GSM strength information
- Cell tower information
Multiple cameras used in the vehicle allow to gather information regarding driver, inside and also surroundings. This data can further enable list of features.
- Front/rear/surrounding camera streaming
- Driver facing camera streaming
- proximity warnings
Services/Solutions Around Data
Data from different sources is captured to turn into meaningful information. Multiple external services are combined together to form complete ecosystem a web of services to add end value to all parties involved.
Diagram below shows some of the services which can be incorporated based on additional information from connected & Autonomous vehicles.
Retrieving vehicle location information enables to develop different mobility service to create complete ecosystem for end consumers.
Build travel information sharing on location information, suggesting flight/train information and sharing near by hotels information to end consumer.
Build taxi/car sharing/pooling/renting/tracking system around the location information, enabling consumers to collaborate on car sharing systems.
Social Media sharing
Enabling users to share travel information, car sharing, possibility to share on social media, share driving statistics .
Enabling users access to music/video information.
Integration with user calendar and information appointment and schedule meeting etc.
The combination of autonomous driving and in-car entertainment could allow drivers to read e-books, communicate with colleagues, watch documentaries, or browse their vacation photos–without fear of their inattention causing a collision.
Usage based insurance for customers, based on your driving pattern discounted quotes available adding financial incentive to consumers.
Retrieving customer locations and targeting location based marketing services.
Ability to get vehicle health information, notifications in case of critical events and possibility to do vehicle life cycle events from single portal enables host of services to end consumers.
Vehicle service management information. Ability to book services and know estimation and cost of vehicle servicing.
Insurance information and Renewal
Insurance renewal notification, insurance quotes and ability to make payment from single portal.
Critical Events handling
Ability to provide notifications and help regarding vehicle health, towing, eCalls in case of crash.
Vehicle Theft detection & prevention
Theft detection with notifications and location tracking etc. Theft prevention in case of remote control, immobiliser etc.
Telematics control unit
Introducing TCU for full list of features and better connectivity and control of vehicle. Ability to provide latest security patches etc.
Multi camera system support
Ability to process data from multiple cameras and provide real time information to consumer.
For maintenance purpose, remotely diagnose your vehicle. Using preventive and prognostics analysis provide list of features regarding vehicle health, traffic etc.
Ability to provide feature for electric vehicle charging.
Provide real time feedback on driving pattern to the consumer. Based on driving data generate scoring for consumer.
Advanced Driver Assistance System (ADAS) can be build based on the information available. Lane change notification based on driving patter can be provided. Fuel usage and estimations, can be reported to consumer.
Augmented reality navigation with live-motion videos, traffic information and road information for accident/construction etc.
Alerting on very close object detection and alerting user. All front/end/surrounding cameras to provide real time information.
Ability to create geo fences. Notification on entry/exist of geo-fences can be used in different scenarios.
Emergency services based on location information can be used to provide help in case of crash incidents.
Seat belt usage
Warning in case of seat belt not used, driving pattern based on frequent faults.
Warning and notifications regarding phone usage while driving vehicle. Driver facing camera streaming data can be used for same.
Frequent lane change
Driving pattern in case lane change is too frequent.
Real time asset tracking and show real time location information of asset.
Fuel consumption and estimations can be shared. Fuel estimations based on driving route and distanced to be traveled based on destination can be used to share near by fuel stations.
Solving the predictive maintenance problem benefits multiple parties Automakers, dealers, customer. Based on DTC information, vehicle health can be predicted.
Based on vehicle parts life cycle/time information and combining same with driving pattern and road conditions etc. preventative analysis can be used for vehicle parts life.
Ability to optimum route planning for efficiency purpose. Alerting in case of route deviations etc.
Machine Learning can be used to provide real value out of captured data. Along with Deep learning list of features can be provided to consumers. Autonomous vehicle to extensively use these techniques to deliver host of services.
Share weather forecast for set destination.
Nearby air quality data can be used to determine internal air conditioning settings to improve the passenger experience
Foglight data can be used by weather service to forecast practical real time weather predictions
Prepare for arrival
Host of services which can be integrated with Smart homes like Open the garage door, turn on the house lights, adjust the home temperature, turn on the sound system and unlock the front door. From connected vehicle the integration between two makes it seamless experience to end consumers.
IOT data search
Geo-location based searched on nearby IOT data, V2V/V2I communication.
Cross domain IOT data usage and services
Creating clustering of vehicles to draw traffic and other information.
Use acceleration data to find road conditions and plan road maintenance accordingly and use in predictions.
Manage urban mobility in better way, provide parking information to consumers. Smart city use cases fit well in these cases. Auto payment for parking charges can be enabled.
Automated RFID electronic toll collection on toll booths on the road.
Hope above list provide some information regarding what kind of data connected and autonomous vehicles share and what host of services can be provided. In the end, the list of services is vast solving different practical and business problems which will just increase in future and new host of services will keep adding to the list.
In the future posts, we will explore how we can use above data and using different data analytics techniques to provide different services. Consumer driving data Trip analysis and predictive analysis of vehicle health based on DTC are few examples we will cover.