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AI Innovation in Manufacturing, Robotics, New Apps on Display at CES

AI was at the center of much innovation on display at the recent CES trade show, with highlights in the manufacturing industry and in robotics. (GETTY IMAGES)

By AI Trends Staff

AI was showcased in many areas at the recent CES trade show in Las Vegas, attended by over 4,400 exhibitors and 170,000 attendees.

In manufacturing, the majors were showing off their AI prowess.

A new washing machine from LG Electronics uses AI to precisely clean clothes. Internal sensors in the AI DD washer detect the load volume and weight as well as the clothing fabric, according to an account in the WSJ Pro. The washing machine’s AI models then compare those details against 20,000 data points to determine the optimal cycle settings for the laundry. A load of T-shirts and pants needs a certain type of wash, temperature and wash time for best results; the AI figures it out and sets it.

John Deere & Co. showed off its See & Spray machine pulled behind a tractor, using vision and machine learning to detect weeds and determine plant health. See & Spray came with Deere’s acquisition of Blue River Technology in 2017 for $305 million. The technology is said to help reduce agrochemical use. The company is suggesting farmers can save up to $30 per acre by using See & Spray. “We’ve got AI in production, on machines, today and there is more coming,” stated John Stone, senior vice president for the Intelligent Solutions Group at Deere.

Mercedes-Benz is developing an AI system for its Sprinter vans to assist workers in loading packages in an optimal way. Expected to be available within a year, Coros—“cargo recognition and organization system”—is intended to help with “last-mile” logistics. Cameras in the van cargo section read package barcodes, then refer to a model that assesses the package size and where it best belongs. A blue light comes on in the shelf section where the package should be placed. The system identifies the package when it is being picked up for delivery as well. If a package does not belong in a vehicle, red lights come on. The hope is to optimize package loading and reduce training costs.

Innovations Exploiting the Power of AI

Innovations were on display among the many exhibitors at CES. An account in Forbes highlighted a selection, including:

Whisk, a smart food platform acquired by Samsung’s innovation-focused subsidiary Samsung Next earlier this year, is now capable of scanning the contents of your refrigerator and suggesting dishes to cook. The AI model refers to research from over 100 nutritionists, food scientists, engineers, and retailers. The company suggests the technology will also help to reduce food waste.

Wiser from Schneider Electric is a small device that monitors energy use by each home appliance in real-time. It installs in the home circuit breaker box; its machine learning models are aimed at optimizing savings, including for solar systems.

A vital signs monitoring app from analyzes a person’s face to detect medical insights. The app detects oxygen saturation, respiration rate, heart rate variability and mental stress. Plans are to add monitoring for hemoglobin levels and blood pressure.

Robots Extending into Homes, Humanoid Forms

Interesting robots incorporating AI was the focus of an account from CES from TechRepublic; including the following examples.

Samsung’s Ballie, still a research project, is a tennis ball-sized life companion, reported ZDNet. Ballie is a small, round, rolling robot designed to support, understand, and react to the needs of its owner, specifically in households. Ballie’s AI capabilities use sensors and data within the home to attempt an immersive experience. The device will be designed to be able to connect with and control other smart devices in the home.

Graphics chipmaker NVIDIA showed its reach in robotics at CES, with its GPU chips used in a number of innovative robots. For example, Toyota’s new humanoid robot T-HR3, along with its Jetson AGX Xavier computer. The T-HR3 uses advanced synchronization and master maneuvering to move smoothly and control the force of its body. The system is controlled by a human operator wearing a virtual reality (VR) headset. T-HR3 receives the data through augmented video and perception data via a NVIDIA’s Jetson AGX Xavier computer within the robot, according to a NVIDIA blog post.

Other NVIDIA-powered robots at CES, cited in an account in ZDNet, included an autonomous wheelchair from WHILL powered by a Jetson TX2, a home security drone from Sunflower Labs, a delivery robot from PostMates and an inspection snake robot from Sarcos.

Read the source articles in WSJ Pro, Forbes and   TechRepublic.

Source: AI Trends
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The Environmental Impacts of AI and IoT In Agriculture

The promise of AI in agriculture is to increase crop yields and lead to more environmentally friendly farming practices. (GETTY IMAGES)

By Caleb Danziger, Science Writer

As the world’s citizenry continues to grow, with estimates putting 2100’s population at 11.2 billion, the agriculture industry will need to compensate for increased demand. Within the next 80 years, an additional 3.6 billion people will need food; production needs to improve beyond what’s possible today. At the same time, land dedicated to agricultural projects may become limited, calling for enhanced efficiency and viability.

IoT and AI solutions can vastly improve crop yields and may be the only way to achieve a better system, according to some experts. The technology can also pave the way for environmentally friendly processes.

AI and IoT for Agricultural Applications

If AI and IoT are the answer, at least in some small form, what will they do? How can the technology integrate into existing operations, and how will it present new opportunities?

  • Precision Farming Through Micro-Sensors: Most farming operations require a keen eye, as farmers scan their crops for signs of disease and contamination. At a macro-level, the process is easy, but the eyes can’t spot everything. With the help of modern IoT solutions, as well as AI and mobile computing, farmers can offset the entire process, relying on technology to do the review. Farmers can monitor Individual plants for potential sickness and disease with the help of micro-sensors. Plus, the technology can display stats remotely via a smartphone or similar device, allowing farmers to see instant alerts about what’s happening in their fields, whether it has to do with pests, disease or something else. Many sensors are already in use in the current market, from mechanical sensors that measure soil compaction and erosion to real-time devices that detect pest populations.
  • Drone Operations and Crop Monitoring: Alongside IoT monitoring—or perhaps in place of it—aerial drones can analyze and monitor crops. Using cameras and sensors embedded inside, the drones gather information about plants down to a single leaf. When fed into a neural network or machine learning solution, all the collected data can provide a detailed image of a farmer’s stock.
  • Smart Collars for Livestock: Cattle and livestock management is no small feat. Not only do farmers have to monitor each animal’s whereabouts accurately, but they also have to stay informed about their health. To alleviate some of the responsibility, farmers have begun equipping their cows with Fitbit-like IoT wearables that monitor data in real-time. Wearable applications can be used on any animals on a farm, including horses, cattle and poultry.
  • AI-Powered Pesticide Applicators: By combining AI control solutions and IoT sensors, farmers can better protect crops from pests. Spot treatment allows farmers to treat plants individually and keep away potential insects. At the same time, fewer chemicals enter the surrounding environment, including the soil underneath.

Smarter Operations Through Data Sharing

AI and neural network solutions can be trained through data ingestion. As a result, technology controlled by AI could see an increase in efficiency over time as the system becomes smarter, contextualized and more aware.

Collectively, experts can use that gathered information to generate predictive models and compare performance statistics to find insights. In the farming world, the data-sharing of thousands of setups and relevant statistics can make for more effective operations across the board.

With data sharing, agricultural experts can share and consume a vast amount of knowledge, everything from soil and seed tests to yield-improving maintenance tips.

The Downside to Modern Technology

AI and IoT will undoubtedly make a significant impact in agriculture. These tech innovations, however, come with potential setbacks, both for farmers and the environment.

  • Increased Cybersecurity Risk: As technology continues to rely on the internet — and more operation-specific data is collected — vulnerabilities and access points will appear. Thieves can steal more than sensitive information. If IoT solutions are in place, remote hackers can seize control of applications. If a hacker were to gain control of a pesticide dispersal system, for example, it could prove disastrous. Theoretically, they could spray more chemicals than needed, poisoning or killing crops. As a preventive, farmers must implement cybersecurity foundationally to prevent potential attacks.
  • High Adoption Costs: IoT-enabled devices and sensors, while not incredibly expensive, can prove pricey when bought in bulk. Along with the hardware, a suitable local network must be put in place to facilitate and support the massive influx of data. Plus, there’s the matter of proper data storage, either locally or cloud-based. AI and big data solutions must also be implemented on the backend to analyze, organize, and extract usable insights from digital content. These requirements can lead to incredibly high adoption costs at even the smallest of agricultural facilities.
  • Environmental Risks: To make matters worse, all new technology requires power to run. A system that supports a large-scale agricultural operation will require massive amounts of energy. Furthermore, many advanced robots and solutions still need fossil fuels to operate, polluting the environment. Without more sustainable energy—or even renewable solutions—IoT and similar modern technologies are not a proper fix for environmental issues. Instead, adoption may cause more problems in the short term.

AI and IoT In Agriculture — The Way Forward

As a society, we have a long way to go when it comes to improving the impact of our actions on the environment. The agricultural field is no exception. Experts won’t see a change tomorrow or in the coming weeks. However, what’s important is that we’re continuously working toward that goal.

Farmers and manufacturers already use IoT and AI technology to increase operational efficiency and reduce waste output. From drone and sensor monitoring to Fitbit-like wearables, the innovations seem endless. As smart devices complete routine tasks, farmers can spend more time on critical matters, such as reducing emissions and their environmental impact.

Technology has been a boon for the agricultural industry, yet it’s also seen some drawbacks. Increasing efficiency often comes with a steep price tag, a cost many small-scale farmers can’t afford. Plus, devices that run on fossil fuels further contribute to climate change. Only time will tell what roles AI and IoT play in the future.

Caleb Danziger is a tech blogger and freelance writer. He co-owns

Source: AI Trends
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