Proximity Marketing – An IoT Based Approach for Improved Results

Introduction

IoT has penetrated many domains and areas and has been successful. It has revolutionized the industry altogether, and this article will reveal the capabilities of IoT for Proximity Marketing. The reader would be able to connect and understand the problem statement and realize the importance of this innovation.

The Problem Statement

With the advent of technologies and smartphones, brick-and-mortar store owners have increasingly seen consumers migrate away from brick-and-mortar retail stores in favor of convenient digital outlets over the last few years. With the ease of smartphones and “one-click” shopping, many shoppers feel that browsing for products in a physical store is almost obsolete. On researching to go over the issue, it is found that BLE Beacons are a great way to guide customers their way through a large store and find the intended product. Also, for owners, it helps in targeted product recommendations. The proposed solution consists of Proximity sensing and a Product recommender system.

Real-Time Pulsar and Python Apps on a Pi

Today we will look at the easy way to build Python streaming applications from the edge to the cloud. Let's walk through how to build a Python application on a Raspberry Pi that streams sensor data and more from the edge to any and all data stores while processing data in event time.

My GitHub repository has all of the code, configuration, and scripts needed to build and run this application.

Easy IoT and Device Management for Non-C Coders

If you have an interest in learning how to program microcontrollers for home monitoring DIY projects or looking at developing commercial IoT products, but lack C code experience, look no further. This hands-on tutorial shows how to get your project up and running really fast using a high level language called Lua. You do not need any C experience, and you can easily install the ready to use the microcontroller firmware by following a few instructions.

Lua - easy for kids to learn and also powerful enough for developing professional IoT solutions!

Optimized File Formats – Reduce Overall System Latency

Since Optimized columnar file formats helped Big data ecosystem to have SQL query features, Organizations are now able to retrain their existing data warehouse or Database developers quickly in Big data technology and migrate their analytics applications to on-premise Hadoop clusters or cheap object storage in the cloud.

When Columnar file formats were first proposed in the early 2010s, the intention was to enable faster query execution engines on top of the Hadoop file system. The columnar format was explicitly designed to give much-improved query performance than conventional row-based file formats. Columnar file formats give much better performance than row-based file formats (used in conventional Databases and data warehouses) when a partial set of columns from a table are queried.