diff --git a/src/main/java/com/github/megachucky/kafka/streams/machinelearning/KsqlUdfDeepLearningMqttIotExample.java b/src/main/java/com/github/megachucky/kafka/streams/machinelearning/KsqlUdfDeepLearningMqttIotExample.java
deleted file mode 100644
index 84cd98b..0000000
--- a/src/main/java/com/github/megachucky/kafka/streams/machinelearning/KsqlUdfDeepLearningMqttIotExample.java
+++ /dev/null
@@ -1,127 +0,0 @@
-/*
- * Licensed to the Apache Software Foundation (ASF) under one or more
- * contributor license agreements.  See the NOTICE file distributed with
- * this work for additional information regarding copyright ownership.
- * The ASF licenses this file to You 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.
- */
-
-package com.github.megachucky.kafka.streams.machinelearning;
-
-import java.io.FileInputStream;
-import java.io.InputStream;
-import java.util.Collections;
-import java.util.Properties;
-
-import org.apache.kafka.common.serialization.Serdes;
-import org.apache.kafka.streams.KafkaStreams;
-import org.apache.kafka.streams.StreamsBuilder;
-import org.apache.kafka.streams.StreamsConfig;
-import org.apache.kafka.streams.kstream.KStream;
-
-
-/**
- * @author Kai Waehner
- */
-public class KsqlUdfDeepLearningMqttIotExample {
-
-	private static final String imageInputTopic = "ImageInputTopic";
-	private static final String imageOutputTopic = "ImageOutputTopic";
-
-	private static final String server = "localhost";
-	private static final Integer port = 9000;
-
-	// Image path will be received from Kafka message to topic 'imageInputTopic'
-	private static String imagePath = null;
-
-	public static void main(String[] args) throws Exception {
-
-		// Configure Kafka Streams Application
-		final String bootstrapServers = args.length > 0 ? args[0] : "localhost:9092";
-
-		final Properties streamsConfiguration = new Properties();
-
-		// Give the Streams application a unique name. The name must be unique
-		// in the Kafka cluster against which the application is run.
-		streamsConfiguration.put(StreamsConfig.APPLICATION_ID_CONFIG, "kafka-streams-tensorflow-serving-gRPC-example");
-
-		// Where to find Kafka broker(s).
-		streamsConfiguration.put(StreamsConfig.BOOTSTRAP_SERVERS_CONFIG, bootstrapServers);
-
-		// Specify default (de)serializers for record keys and for record
-		// values.
-		streamsConfiguration.put(StreamsConfig.DEFAULT_KEY_SERDE_CLASS_CONFIG, Serdes.String().getClass().getName());
-		streamsConfiguration.put(StreamsConfig.DEFAULT_VALUE_SERDE_CLASS_CONFIG, Serdes.String().getClass().getName());
-
-		// In the subsequent lines we define the processing topology of the Streams
-		// application.
-		final StreamsBuilder builder = new StreamsBuilder();
-
-		// Construct a `KStream` from the input topic "ImageInputTopic", where
-		// message values represent lines of text
-		final KStream<String, String> imageInputLines = builder.stream(imageInputTopic);
-		
-		
-		KStream<String, Object> transformedMessage = imageInputLines.mapValues(value -> {
-
-			System.out.println("Image path: " + value);
-
-			imagePath = value;
-
-//			TensorflowObjectRecogniser recogniser = new TensorflowObjectRecogniser(server, port);
-
-			System.out.println("Image = " + imagePath);
-			InputStream jpegStream;
-			try {
-				jpegStream = new FileInputStream(imagePath);
-				
-				// Prediction of the TensorFlow Image Recognition model:
-//				List<Map.Entry<String, Double>> list = recogniser.recognise(jpegStream);
-//				String prediction = list.toString();
-//				System.out.println("Prediction: " + prediction);
-//				recogniser.close();
-				jpegStream.close();
-   
-//                                 return prediction;
-				return null;
-			} catch (Exception e) {
-				e.printStackTrace();
-      
-                                 return Collections.emptyList().toString();
-			}
-
-		});
-		
-
-
-		// Send prediction information to Output Topic
-		transformedMessage.to(imageOutputTopic);
-
-		// Start Kafka Streams Application to process new incoming images from the Input
-		// Topic
-		final KafkaStreams streams = new KafkaStreams(builder.build(), streamsConfiguration);
-
-		streams.cleanUp();
-
-		streams.start();
-
-		System.out.println("Image Recognition Microservice is running...");
-
-		System.out.println("Input images arrive at Kafka topic " + imageInputTopic + "; Output predictions going to Kafka topic "
-				+ imageOutputTopic);
-
-		// Add shutdown hook to respond to SIGTERM and gracefully close Kafka
-		// Streams
-		Runtime.getRuntime().addShutdownHook(new Thread(streams::close));
-
-	}
-}