Consider the consecutive value in the data

I have a data with 3 columns ID, Time and Type; I Need to add a column called "categroy" and the sample data with output is given below:

> dput(DF1)
structure(list(ID = c("104 - 2019-06-03", "104 - 2019-06-03", 
"104 - 2019-06-03", "104 - 2019-06-03", "104 - 2019-06-03", "104 - 2019-06-03", 
"104 - 2019-06-03", "104 - 2019-06-03", "104 - 2019-06-03", "104 - 2019-06-03", 
"104 - 2019-06-03", "111 - 2019-05-31", "111 - 2019-05-31"), 
    Time = c("11:17:01", "12:48:51", "13:54:09", "14:14:46", 
    "14:19:46", "14:32:46", "14:19:27", "14:35:12", "15:30:22", 
    "15:31:22", "16:29:12", "09:31:53", "09:31:56"), Type = c("IN", 
    "Out", "IN", "IN", "IN", "IN", "Out", "Out", "IN", "IN", 
    "Out", "IN", "Out"), Category = c("Include", "Include", "Include", 
    "Exclude", "Exclude", "Exclude", "Exclude", "Include", "Include", 
    "Exclude", "Include", "Include", "Include")), row.names = c(NA, 
-13L), class = c("tbl_df", "tbl", "data.frame"))

Being a swipe data sorted based on time and ID, need to consider if the person is marked as "IN" and then "Out" makes it a one proper entry. I mark both the IN and OUT as "Include" if it happens sequentially. Sometime, there are multiple consecutive IN and OUT entry and in those cases I mark the First "IN" as include and the "last "OUT" as include. The in between entries are marked as exclude. Thanks!