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Best home security camera (2022)

ZDNet

Security is imperative for companies to deter trespassers and would-be thieves and to protect valuable equipment crucial for businesses to operate successfully. A robust setup with cameras, sensors, and night vision can take the pressure off security teams and give business owners peace of mind out-of-hours. Luckily for organizations, the emergence of the Internet of Things (IoT) technology, mobile connectivity, apps, and cloud technologies has radically changed the security landscape and made it easier than ever to set up multi-room and on-premise systems. The possibilities are endless: cloud or local feed storage, customizable or automatic alerts and alarms, smartphones and tablet connectivity, wired or wireless, battery-powered or mains options, video capture, night vision, audio feeds of varying quality, and the ability to check-in, in real-time, are all on offer and can be tailored depending on the requirements of your business. To make navigating the variety of hardware and vendor ecosystems available to today's company owners less of a challenge, we have assembled our top ten picks for businesses.


3 Challenges to the Universal Adoption of AI

#artificialintelligence

The use of connected smart devices is growing rapidly, but they are not yet everywhere. There are 3 challenges to the universal adoption of AI. As you may have already realized, AI has influenced your life. And its impact is only going to grow from here. Achieving a future of ubiquitous AI could be life-changing.


Artificial Intelligence Is the Next Step for Smart Homes

#artificialintelligence

In recent years, homeowners have adopted smart home technologies to improve their quality of life. Connected devices and appliances perform actions, tasks, and automated routines based on a homeowner's preferences. Smart technologies enable homeowners to save time, money, and energy. Major tech companies such as Apple, Google, and Amazon have driven the adoption of smart home technologies. From digital voice assistants to intelligent thermostats and everything in between, smart homes are the homes of the future.


What is Artificial Intelligence of Things (AIoT)? - Definition from WhatIs.com

#artificialintelligence

The Artificial Intelligence of Things (AIoT) is the combination of artificial intelligence (AI) technologies with the Internet of Things (IoT) infrastructure to achieve more efficient IoT operations, improve human-machine interactions and enhance data management and analytics. AI can be used to transform IoT data into useful information for improved decision making processes, thus creating a foundation for newer technology such as IoT Data as a Service (IoTDaaS). AIoT is transformational and mutually beneficial for both types of technology as AI adds value to IoT through machine learning capabilities and IoT adds value to AI through connectivity, signaling and data exchange. As IoT networks spread throughout major industries, there will be an increasingly large amount of human-oriented and machine-generated unstructured data. AIoT can provide support for data analytics solutions that can create value out of this IoT-generated data.


The Rational Selection of Goal Operations and the Integration ofSearch Strategies with Goal-Driven Autonomy

arXiv.org Artificial Intelligence

Intelligent physical systems as embodied cognitive systems must perform high-level reasoning while concurrently managing an underlying control architecture. The link between cognition and control must manage the problem of converting continuous values from the real world to symbolic representations (and back). To generate effective behaviors, reasoning must include a capacity to replan, acquire and update new information, detect and respond to anomalies, and perform various operations on system goals. But, these processes are not independent and need further exploration. This paper examines an agent's choices when multiple goal operations co-occur and interact, and it establishes a method of choosing between them. We demonstrate the benefits and discuss the trade offs involved with this and show positive results in a dynamic marine search task.


ARTIFICIAL INTELLIGENCE: Then, Now, and What to Expect in the Age of IoT

#artificialintelligence

Artificial Intelligence (AI) has a strong relationship with Information and Communications Technology (ICT). Increasingly integrated with and/or supporting various aspects of computing and networking, AI is also anticipated to become increasingly important in terms of support for digital assets as well as physical infrastructure. The following are excerpts from the article by Gerry Christensen, "ARTIFICIAL INTELLIGENCE: Then, Now, and What to Expect in the Age of IoT", written for the March/April 2019 edition of BICSI's ICT Today periodical: "In the not-so-distant future, if not tomorrow, you will awaken feeling refreshed and alert from a good night's sleep in a smart home with automatically adjusted temperature and lighting. Enjoy breakfast in a smart kitchen with a smart refrigerator that never forgets to order more milk or OJ. Head out for your morning run wearing an IoT-enabled athletic shirt that provides real-time biometric readings. And then drive your smart car to the smart city where you will undoubtedly do smart work in a smart building," predicts Jeff Klaus, general manager of data center software at Intel.


Manufacturing Shifts To AI Of Things

#artificialintelligence

AI is being infused into the Internet of Things, setting the stage for significant improvements in manufacturing productivity, improved uptime, and reduced costs -- regardless of market segment. The traditional approach to improving manufacturing equipment reliability and efficiency is regular scheduled maintenance. While that is an improvement over just fixing or replacing equipment when it breaks, it's far from optimal. Even with periodic maintenance, equipment can suddenly break down, idling workers, delaying shipments, and disappointing customers. This is where AI fits in.


Voice AI Predictions for 2022 from 25 Industry Leaders - Voicebot.ai

#artificialintelligence

How will voice AI develop in 2022? More than 25 voice industry pros offer your predictions for the coming year. There will be more enterprise focus as a continuing trend of 2021, more custom assistants, and several new developments related to the metaverse. This past year was an important transition year for the voice AI market as Brandon Kaplan and Pete Erickson aptly highlight. Consumer applications and the general-purpose consumer assistants from the tech giants drove interest in the market for many years, but that changed in 2021 as enterprise use cases and customer, brand-owned assistants took center stage.


Why 'Skyrim' still matters a decade later

Mashable

With the exception of a rare few, video games are notoriously ephemeral things. Far more than in film, TV, or music, even the greatest achievements in games are all but guaranteed rapid obsolescence. Beholden to the ever-evolving technology that powers them, it's hard for any game to withstand the test of a single console cycle, let alone sustain large, active player communities for a double-digit number of years. For story-focused single-player adventures that don't live online, the feat is practically unheard of. But one iconic title celebrating its 10-year anniversary in 2021 flies in the face of those norms, like a legendary dragon soaring through the sky with the roar of a creature that never truly dies: The Elder Scrolls V: Skyrim.


A Neurorobotics Approach to Behaviour Selection based on Human Activity Recognition

arXiv.org Artificial Intelligence

Behaviour selection has been an active research topic for robotics, in particular in the field of human-robot interaction. For a robot to interact effectively and autonomously with humans, the coupling between techniques for human activity recognition, based on sensing information, and robot behaviour selection, based on decision-making mechanisms, is of paramount importance. However, most approaches to date consist of deterministic associations between the recognised activities and the robot behaviours, neglecting the uncertainty inherent to sequential predictions in real-time applications. In this paper, we address this gap by presenting a neurorobotics approach based on computational models that resemble neurophysiological aspects of living beings. This neurorobotics approach was compared to a non-bioinspired, heuristics-based approach. To evaluate both approaches, a robot simulation is developed, in which a mobile robot has to accomplish tasks according to the activity being performed by the inhabitant of an intelligent home. The outcomes of each approach were evaluated according to the number of correct outcomes provided by the robot. Results revealed that the neurorobotics approach is advantageous, especially considering the computational models based on more complex animals.