Calculate differences between consecutive Kafka messages in one Topic - apache-kafka

Question

I have some temperature sensors which are generated Kafka messages to a Kafka topic (my-sensors-topic). The messages generally look like below.
{"Offset": 7, "Id": 1, "Time": 1643718777898, "Value": 21}
{"Offset": 6, "Id": 1, "Time": 1643718768592, "Value": 20}
{"Offset": 5, "Id": 2, "Time": 1643718755443, "Value": 21}
{"Offset": 4, "Id": 3, "Time": 1643718746678, "Value": 21}
{"Offset": 3, "Id": 4, "Time": 1643718733408, "Value": 22}
{"Offset": 2, "Id": 2, "Time": 1643718709450, "Value": 20}
{"Offset": 1, "Id": 3, "Time": 1643718667375, "Value": 22}
{"Offset": 0, "Id": 1, "Time": 1643718386944, "Value": 19}
What I want to do is for a new generated message:
{"Offset": 8, "Id": 2, "Time": 1643719318393, "Value": 21}
Firstly compare the "Time" differences (in milliseconds) with the last existed message that has the same Id. In this case:
{"Offset": 5, "Id": 2, "Time": 1643718755443, "Value": 21}
Because its the last existed message and also with Id 2.
Secondly, I want to subtract the "Time" differences between these two messages.
If the difference is greater than 60000, then it's counted as an error occurred for this sensor and I need to create a message to record the error and write the message to another Kafka topic (my-sensors-error-topic).
The created message perhaps look like:
{"Id": 2, "Time_lead": 1643719318393, "Time_lag": 1643718755443, "Letancy": 1562950}
//Latency is calculated by (Time_lead-Time_lag)
So later I can select the Count from my-sensors-error-topic by (sensor) Id so I know how many errors occurred for this sensor.
From my own investigation, to reach my scenario, I need to use Kafka Processor API with State Store. Some examples mentioned I can implement Processor interface while others mentioned using Transform.
Which way is better to implement my scenarios and how?