--- /dev/null
+# ==================================================================================
+# Copyright (c) 2020 HCL Technologies Limited.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+# http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+# ==================================================================================
+
+
+Anomaly Detection Overview
+======================
+
+Anomaly Detection (AD) is an Xapp in the Traffic Steering O-RAN use case,
+which uses the following Xapps:
+
+#. AD, which iterates per second, fetches UE data from .csv files and send prediction to Traffic Steering
+#. Traffic Steering send acknowldgement back to AD.
+
+Expected Input
+--------------
+
+The AD Xapp expects a prediction-input in following structure::
+
+UEPDCPBytesDL UEPDCPBytesUL UEPRBUsageDL UEPRBUsageUL S_RSRP S_RSRQ S_SINR N1_RSRP N1_RSRQ N1_SINR N2_RSRP N2_RSRQ N2_SINR UEID ServingCellID N1 N2 MeasTimestampRF
+
+ 300000 123000 25 10 -43 -3.4 25 -53 -6.4 20 -68 -9.4 17 12345 555011 555010 555012 30:17.8
+
+
+Expected Output
+---------------
+
+The AD Xapp should send a prediction for Anomulous UEID along with timestamp
+as a JSON message via RMR with the following structure:
+
+ {
+ "UEID" : 12371,
+ "MeasTimestampRF" : "2020-11-17 16:14:25.140140"
+ }
+
+
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