diff --git a/rules/preprocessing.snakefile b/rules/preprocessing.snakefile
index 20b92301..1eae30f8 100644
--- a/rules/preprocessing.snakefile
+++ b/rules/preprocessing.snakefile
@@ -30,4 +30,15 @@ rule phone_valid_sensed_days:
     output:
         "data/interim/{pid}/phone_valid_sensed_days.csv"
     script:
-        "../src/data/phone_valid_sensed_days.R"
\ No newline at end of file
+        "../src/data/phone_valid_sensed_days.R"
+
+rule unify_ios_android:
+    input:
+        sensor_data = "data/raw/{pid}/{sensor}_with_datetime.csv",
+        participant_info = "data/external/{pid}"
+    params:
+        sensor = "{sensor}"
+    output:
+        "data/raw/{pid}/{sensor}_with_datetime_unified.csv"
+    script:
+        "../src/data/unify_ios_android.R"
\ No newline at end of file
diff --git a/src/data/unify_ios_android.R b/src/data/unify_ios_android.R
new file mode 100644
index 00000000..7136421f
--- /dev/null
+++ b/src/data/unify_ios_android.R
@@ -0,0 +1,70 @@
+source("packrat/init.R")
+
+library(dplyr)
+
+unify_ios_calls <- function(ios_calls){
+    # Android’s call types 1=incoming, 2=outgoing, 3=missed
+    # iOS' call status 1=incoming, 2=connected, 3=dialing, 4=disconnected
+    # iOS' call types based on call status: (1,2,4)=incoming=1, (3,2,4)=outgoing=2, (1,4) or (3,4)=missed=3
+    # Sometimes (due to a possible bug in Aware) sequences get logged on the exact same timestamp, thus 3-item sequences can be 2,3,4 or 3,2,4
+    # Even tho iOS stores the duration of ringing/dialing for missed calls, we set it to 0 to match Android
+
+    ios_calls <- ios_calls %>%
+        arrange(trace, timestamp, call_type) %>% 
+        group_by(trace) %>%
+                # search for the disconnect event, as it is common to outgoing, received and missed calls
+        mutate(completed_call = ifelse(call_type == 4, 2, 0), 
+                # assign the same ID to all events before a 4
+                completed_call = cumsum(c(1, head(completed_call, -1) != tail(completed_call, -1))), 
+                # hack to match ID of last event (4) to that of the previous rows
+                completed_call = ifelse(call_type == 4, completed_call - 1, completed_call)) %>% 
+        summarise(call_type_sequence = paste(call_type, collapse = ","), # collapse all events before a 4
+                    # use this if Android measures calls' duration from pick up to hang up
+                    # duration = last(call_duration), 
+                    # sanity check, timestamp_diff should be equal or close to duration sum
+                    # timestamp_diff = trunc((last(timestamp) - first(timestamp)) / 1000) 
+                    # use this if Android measures calls' duration from dialing/ringing to hang up
+                    call_duration = sum(call_duration), 
+
+                    timestamp = first(timestamp),
+                    utc_date_time = first(utc_date_time),
+                    local_date_time = first(local_date_time),
+                    local_date = first(local_date),
+                    local_time = first(local_time),
+                    local_hour = first(local_hour),
+                    local_minute = first(local_minute),
+                    local_day_segment = first(local_day_segment)
+                    ) %>% 
+        mutate(call_type = case_when(
+            call_type_sequence == "1,2,4" | call_type_sequence == "2,1,4" ~ 1, # incoming
+            call_type_sequence == "1,4" ~ 3, # missed
+            call_type_sequence == "3,2,4" | call_type_sequence == "2,3,4" ~ 2, # outgoing
+            call_type_sequence == "3,4" ~ 4, # outgoing missed, we create this temp missed state to assign a duration of 0 below
+            TRUE ~ -1), # other, call sequences without a disconnect (4) event are discarded
+            # assign a duration of 0 to incoming and outgoing missed calls
+            call_duration = ifelse(call_type == 3 | call_type == 4, 0, call_duration), 
+            # get rid of the temp missed call type, set to 3 to match Android
+            call_type = ifelse(call_type == 4, 3, call_type) 
+        ) %>% 
+        # discard sequences without an event 4 (disconnect)
+        filter(call_type > 0) %>%
+        ungroup() %>%
+        arrange(timestamp)
+
+    return(ios_calls)
+}
+
+
+sensor_data <- read.csv(snakemake@input[["sensor_data"]], stringsAsFactors = FALSE)
+participant_info <- snakemake@input[["participant_info"]]
+sensor <- snakemake@params[["sensor"]]
+platform <- readLines(participant_info, n=2)[[2]]
+
+if(sensor == "calls"){
+    if(platform == "android"){
+        write.csv(sensor_data, snakemake@output[[1]], row.names = FALSE)
+    } else if(platform == "ios"){
+        sensor_data = unify_ios_calls(sensor_data)
+        write.csv(sensor_data, snakemake@output[[1]], row.names = FALSE)
+    }
+}