IoT is transforming every sector of society and healthcare systems are no exceptions. Certainly, IoT based smart applications can handle large volumes of data efficiently. On the other hand, Machine Learning (ML) techniques provide us meaningful insights. Without a doubt, we can realize the benefits of IoT and Machine Learning in Smart Healthcare. The innovative … Read more
A smart city should adopt appropriate ways of sanitation. Building Cities with Smart Sanitation will not only bring smart technologies into sanitation systems but will also help in identifying the early signs of an outbreak of a disease. Sanitation facilities play a major role in affecting the health conditions of people. Hence, Appropriate measures in … Read more
To begin with this discussion, we can say that as a new field in Machine Learning, Federated Learning has to overcome many challenges. In this post on Challenges in Adopting Federated Learning, I will highlight the open issues and challenges that we still have to overcome. Basically, Federated Learning is a new kind of Machine … Read more
In this post on Privacy and Security Mechanisms for Federated Learning, I will discuss some of the mechanisms for achieving the privacy in Federated Learning approach. Although, these issues are still the topic of research, yet few techniques are emerging that we can use in preserving the privacy of user data. Why Privacy Mechanisms are … Read more
In this post on Prominent Applications of Deep Learning in Agriculture, I will discuss 10 significant application scenarios. In fact, all such applications can greatly benefit from Deep Learning Techniques. What is Deep Learning? Deep Learning is a subset of machine learning. Mainly Deep Learning comprises techniques that take inspiration from the way how the … Read more
In this post on Federated Learning Architectures and Their Applications, I will talk about various architectures for implementing Federated Learning and application scenarios of each of them. In my earlier post on Federated Learning, I have discussed the basic concepts and pros and cons of this new technique of building machine learning models. However, when we … Read more
In this post on Collaborating Model Training using Federated Learning, I will explain how the training of a neural network occurs without the need of collecting the whole training data on a centralized location. Basically, Federated Learning is a special form of Machine Learning, which requires the model training at local participants’ location and only … Read more
Data Science offers a number of techniques that help you analyze IoT data. Basically, there are a number of programming languages that you can use for applying data science techniques including Python, R, and JavaScript. However, Python remains the most widely used language among others. This because the language contains many libraries that make our … Read more
As the popularity of smart homes and smart appliances increases so is the need of analyzing the data that these devices generate. The sensors working in these smart appliances constantly generate data which quickly takes high volume. In this post on How Internet-of-Things (IoT) is related to Data Science, you will understand the need for … Read more
In this post on Motor Selection in Robotics, you will learn about different types of motors that the robots use and which type of motor is best suitable for a particular robot. Basically, the motor is an essential component of a robot and is responsible for making a robot move. Every robot exhibits some kind … Read more
