Edge computing offers economic benefits for organizations. This is because of carrying out computing closer to the edge of the network and it helps organizations to analyze significant data in real-time. Edge computing is useful for across many industries or organizations such as manufacturing, automotive, telecommunications, healthcare, and finance among others.
Automobile makers are focused on edge computing to address these ever-evolving challenges. A group of cross-industry global players has formed the Automotive Edge Computing associating to drive best practices for the merging between the vehicle and computing ecosystem. Let’s see how we can resistant edge computing in the automobile sector.
Some of the Use Cases of Edge computing in Automotive :
Edge Computing offers variety of use cases in automotive industry right from sensors, applications to the user experience. Now lets begin with some of the possible use cases of Edge computing in automotive industry. Use cases of Edge computing are as follows :
1. SENSOR DATA - LESS IS MORE
In general, there are various sensors built-in everyday smart devices and from a proximity sensor in smartphones to smoke sensors in intelligent houses. These sensors differentiate themselves by type, technology, etc. Moreover, they all have one common element, which is called as “Data,” and it is generated in large quantities.
This same process is applied to vehicles and a typical luxury vehicle contains hundreds of sensors. With Edge computing, data pushed to cloud could be limited more smartly and can process and analyse the data at the edge and only select non-sensitive data can be transferred to the cloud. This brings data transmission costs get reduce and also protects the sensitive data leaving the vehicle.
2. ELECTRIC VEHICLE
The two types of Electric vehicle are given below :
a. Battery monitoring and Predictive maintenance
The battery of electric vehicles needs to deliver throughput in the best possible ways and to achieve this, continuous monitoring and predictive maintenance of battery are required. The health of battery depends on various factors like driver habits, acceleration, traffic conditions, charging cycles, and so on. Edge computing can aggregate all this data and perform a real-time inspection of key battery parameters and alert the vehicle owner in case of any deviation.
b. Charging stations - Predict and plan
Edge computing plays a vital role in overall planning & optimization of charging processes, including wait time at the queue, fare, etc. This, in turn, helps in achieving greater efficiency for charging stations and thus, overall mobility.
3. SMART TRAFFIC MANAGEMENT
Consider a real-life scenario at a traffic stop, especially junction of five-six roads which are heavily used most times. Only the vehicle would not control the long waiting times as it requires to follow the traffic norms. But, let’s consider a futuristic scenario if the road intersection has an edge device deployed to which all vehicles can communicate while coming towards the intersection. The edge device can aggregate the data from vehicles which are nearby and also send notification to them advance about the situation at the intersection. Therefore, edge computing increases efficiency and throughput at the complex road intersections.
4. VEHICLE SECURITY - MULTI LEVEL AUTHENTICATION
Multi-level authentication could having multiple sensors like cameras, proximity sensors and many more. The aggregated data from these edge devices could be used to enable multi-level authentication in which the camera will be used for face recognition, Bluetooth sensor to detect the proximity of driver’s phone, and an infrared camera.
5. PREDICTIVE MAINTENANCE
Edge computing can continuously check the various parameters of the vehicle, such as temperature, mileage, tire inflation, braking, acceleration, and speed. The analytics model will predict if any component will likely to fail and alert the vehicle owner. For example- Tire pressure below the safe level. Edge device will remind the vehicle owner for replacement of the tire.
Benefits of Edge Computing
Achieve higher processing speed : Processing data closer to the source reduces network latency thus increases network performance and speed for end-user.
Increased Security : More data processed at the local device, therefore, which reduces security attacks which happen during data transfer over the network. Also, as it distributes processing, storage, and applications across a range of devices to lower the security risks significantly.
Cost Saving : As edge computing retains most of the data at the device itself, it reduces the network latency which directly translates into dollars.
Super reliability : Local storage and process ensures continuous operations & does not impact just because of most common issues like lost connectivity to the cloud.
Scalability : Computing, storage, and analytics capabilities into devices, edge computing enables companies to scale-up their solutions reach and skills quickly and efficiently
Conclusion.
0 Comments