We are in the booming phase of the Internet of Things (IoT) and, with it, beginning to be aware of the security risks it is vulnerable to. These historical IoT security hacks should give us some perspective: Between 2006–2010, attackers created the Stuxnet virus, designed to damage Iranian centrifuges by targeting their SCADA systems. In 2013, hackers were able to exploit and utilize millions of IoT devices to create a botnet. More than 25% of the zombies in the botnet were made up of devices like smart TVs and baby monitoring systems. In 2015, researchers hacked into a running JEEP’s computer system, managed to engage/disengage the brakes, and cut the driver off his own car.
In our previous posts, we discussed sensors and wireless communications—the two components that underpin the Internet of Things technology. Our current post looks at how these technologies take effect in real life and help make a difference to operations. Two of these cases deal with real-time location systems (RTLS) implemented in healthcare and logistics and the other with condition monitoring in wind farms. (more…)
The holiday season is around the corner and with it comes “Shopping Days”. Over the years, retailers have engineered such days that promise knockout deals to get shoppers into stores in hordes.
In the US, Thanksgiving has given rise to Black Friday and Cyber Monday (BFCM), which are fast spreading across the Atlantic. Barentain Dei (Valentine’s Day) in Japan is followed up with White Day thanks to the ploy of Japanese confectionery companies. In India, Friendship Day and Diwali herald the shopping frenzy while China has its own shopping day in November called Singles Day. Click Frenzy, the Australian version of Cyber Monday, is the brainwave of yet another online retailer.
With holiday shopping days established, retailers need to be prepared to make the most of it. More than 70% of consumers in the US, UK, Canada, and Germany will shop on 2018 Black Friday, predicts a research report by McKinsey. Your branded website could be the top sales channel during these shopping holidays. Here is what we think every eCommerce site should invest in to make the most of the shopping holidays.
The Internet of Things would not be the exciting prospect that it is without a key component – wireless technologies. These technologies are defined under various standards and protocols and choosing the right one depends on the context and the requirement.
Some IoT implementations require data to be transmitted over long distances, others short; some devices transfer small volumes of data, others large. Some are deployed in inaccessible environment and their life needs to be sustained longer. This diversity in requirements and devices necessitates different communication standards and protocols in different contexts.
Twenty eight years ago, the Internet took over the world by storm and turned it to the global village we know today. Enter the Internet of Things, and there are more sentient objects in that village—8.4 billion as per Gartner. Everything from industrial pumps and wind turbines to self-driving cars and household appliances now share the digital space with us. By 2020, their number is set to touch 20 billion.
The connected world may be shrinking by the day, but the digital universe is expanding at a mind-boggling rate. Organizations now handle data in the range of terabytes and petabytes. This data looks nothing like what RDBMS traditionally dealt with. New distributed databases, known by the umbrella term NoSQL, help in the efficient handling of this unstructured and scaling data.
In Part 1 of this series, we learnt how to set up a Hadoop cluster on Azure HDInsight and run a Spark job to process huge volumes of data. In most practical scenarios, however, such jobs are executed as part of an orchestrated process or workflow unless the need is for a one-time processing. In our specific use case, we had to derive different metrics related to error patterns and usage scenarios from the log data and report them on a daily basis.
Before we delve into the interesting part, let me set the context first. The problem we had in hand was to do some data crunching on the log data for one of our client applications, to analyze and report on the various client-defined metrics from the application logs. The application under consideration had a user base of more than 100K users, which meant millions of rows of data to process on a daily basis. Clearly, we were dealing with “big data.” Considering the volume of data involved, we decided to go with Spark running on an Azure HDInsight cluster to benefit from the increased performance offered by Spark’s in-memory RDDs (Resilient Distributed Datasets).
In the face of growing healthcare challenges such as an aging population, chronic diseases, and high cost of hospitalization, wearable patient monitoring (WPM) systems create new opportunities for improving patient care.
From modish wearables that track general fitness, these systems have matured to medical-grade devices that can monitor chronic diseases and other medical conditions. Wearables fitted with advanced biosensors and integrated with a robust IoT platform for analysis and communication constitute a potential solution for early detection of clinical deterioration, timely response by medical staff, and appropriate medical intervention. (more…)