Exploration of ongoing research and advancements in mobility modeling.Identification of areas for improvement in both Markovian and Gravity models.Potential integration with emerging technologies like machine learning and big data analytics.

Sure, I can help with that. Here's a step-by-step approach to your question:

1. Exploration of ongoing research and advancements in mobility modeling: Start by conducting a comprehensive literature review on the current research and advancements in mobility modeling. This can be done by searching for recent articles, journals, and publications related to mobility modeling. Look for new methodologies, techniques, and models that are being used in this field.

2. Identification of areas for improvement in both Markovian and Gravity models: After understanding the current landscape of mobility modeling, identify the limitations or areas of improvement in Markovian and Gravity models. This could be in terms of accuracy, efficiency, scalability, etc. You can do this by critically analyzing the models and also by comparing them with other models.

3. Potential integration with emerging technologies like machine learning and big data analytics: Once the areas of improvement are identified, explore how emerging technologies like machine learning and big data analytics can be integrated to enhance these models. For instance, machine learning algorithms can be used to predict mobility patterns more accurately, while big data analytics can help in handling and processing large volumes of mobility data.

Remember, each of these steps requires a good understanding of mobility modeling and the associated technologies. So, make sure to invest time in learning and understanding these concepts.