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“The blockchain is an incorruptible digital ledger of economic transactions that can be programmed to record not just financial transactions but virtually everything of value.”

Hearing Blockchain everywhere?? Same here.. Let's have a sneak peek into what it is exactly.. !!

National Security Optical sensors like lidar (light detection and ranging) along with UAVs or drones could be used for efficient and reliable security applications. A lidar sensor mounted on a UAV along with sophisticated software can process images for analysis.

Sensors for Security Applications

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A host of devices utilise Wi-Fi (IEEE 802.11), Zigbee 802.15.4 and Bluetooth products in smart thermostats, smoke and CO alarms, security system as well as routers, sensors, appliances and door locks, light switches, gaming consoles and televisions.

Controlling Devices Wirelessly

👉 Bluetooth Low Energy (BLE) is globally interoperable on 2.4GHz band, and is available on all smartphones and tablets. 👉 Recent standard evolutions with Bluetooth 5 as well as BLE Mesh make the technology even more suitable in a smart home. 👉 Bluetooth 5 gives double data throughput (2Mbps), which means that communication through an app is faster. 👉 BLE also results in more power-efficient solutions. For example, a battery-driven sensor can send data much faster and then go to sleep, thus saving battery. 👉 Bluetooth 5 also increases coverage as the range between devices can be four times that of BLE 4.2, all due to the new BLE long-range coding scheme.

👉 LoRaWAN is a wireless technology is extensively used in home automation. 👉 The application ranges from door/window motion sensing, temperature sensing, carbon monoxide monitoring, water metering, gas metering and more. 👉 LoRaWAN gateways with integrated Wi-Fi are already available. This will further augment the use cases for high data rates as well as low data devices and battery-powered sensors.

👉 LTE Small Cell technology provides complete, strong in-home wireless network coverage to support the implementation of home automation.  👉 It extends LTE mobile coverage to small, hard-to-reach areas. 👉 The solution supports up to eight active users and 24 RRC connected users. It is ideal for small homes and offices, and small public hotspots.

Latest wireless technologies for better connectivity

👉 A recommendation system narrows down a list of choices for each user, based on their browsing history, ratings, profile details, transaction details, cart details and so on. Such a system provides useful insights about customers shopping patterns. 👉 Each user is given a personalized view of the eCommerce website based on his/her profile and this allows them to select relevant products. 👉 For example, if you’re looking for a new laptop on Amazon, you might also want to buy a laptop bag. Based on such associations, Amazon will recommend more products to you.

Use case of Data Science and Machine Learning - Recommendation Engine 👉 Surely, you all have used Amazon for online shopping. Have you noticed that when you look for a particular item on Amazon, you get recommendations for similar products? Well, how does Amazon know this? 👉 The reason why companies like Amazon, Walmart, Netflix, etc are doing so well is because of how they handle user-generated data.

Data Science involves the extraction of knowledge from data. In order to do so, it uses a bunch of different methods from various disciplines, like Machine Learning, AI and Deep Learning. A point to note here is that Data Science is a wider field and does not exclusively rely on these techniques.

Fields Of Data Science Data Science covers a wide spectrum of domains, including Artificial Intelligence(AI), Machine Learning and Deep Learning. Data Science uses various AI, Machine Learning and Deep Learning methodologies in order to analyse dataand extract useful insights from it. Definition of these terms are as below : Artificial Intelligence: Artificial Intelligence is a subset of Data Science which enables machines to stimulate human-like behavior. Machine Learning: Machine learning is a sub-field of Artificial Intelligence which provides machines the ability to learn automatically & improve from experience without being explicitly programmed. Deep Learning: Deep Learning is a part of Machine learning that uses various computational measure and algorithms inspired by the structure and function of the brain called artificial neural networks.