Collaborating Authors


(PDF) A Simulation Model for Pedestrian Crowd Evacuation Based on Various AI Techniques


C.W.O, OBOE were 61.78, 30.64, and (aside, wait) for No1A C.W.O, and O.B.D.E significantly more occurred than in OBDE, and evacuation time was recorded as 61.728, 30.864, However, the C.W.A is better to be compared to C.W.A

A Simulation Model for Pedestrian Crowd Evacuation Based on Various AI Techniques Artificial Intelligence

This paper attempts to design an intelligent simulation model for pedestrian crowd evacuation. For this purpose, the cellular automata(CA) was fully integrated with fuzzy logic, the kth nearest neighbors (KNN), and some statistical equations. In this model, each pedestrian was assigned a specific speed, according to his/her physical, biological and emotional features. The emergency behavior and evacuation efficiency of each pedestrian were evaluated by coupling his or her speed with various elements, such as environment, pedestrian distribution and familiarity with the exits. These elements all have great impacts on the evacuation process. Several experiments were carried out to verify the performance of the model in different emergency scenarios. The results show that the proposed model can predict the evacuation time and emergency behavior in various types of building interiors and pedestrian distributions. The research provides a good reference to the design of building evacuation systems.

Thought Leaders in Artificial Intelligence: Allied Universal CIO Mark Mullison (Part 2) Sramana Mitra


Sramana Mitra: Can you take us through some use cases in your customer scenarios where you are seeing these kinds of impact? Mark Mullison: Just a little more context and then I'll get to the specifics. There are three big differentiators in Helios's platform. The first is a proprietary attribute model that we use to store all the knowledge about the site. We organize that in a special way.

Robots are taking over China's food service industry, and making it better · TechNode


At a café called Ratio in Shanghai, a revolving, jointed robot arm with two fingerlike prongs knows just how you like your latte. That's because customers can order via a mini-app on social media platform WeChat, specifying the level of sweetness and choosing between coffee beans. Plus, because it syncs with your social media profile, the barista never spells your name wrong. Robots in restaurants sound like a futuristic novelty. But in China, kitchen-side automation has long been routine for some restaurants, fast food chains, and cafeterias.

San Francisco has news for future tech workers: your days of free lunch may be numbered

USATODAY - Tech Top Stories

The first black female mayor of San Francisco made history Wednesday as she took the oath of office, vowing to help drug users and the homeless in a city known for extreme wealth and poverty. Facebook offers a typical tech company perk for its employees: free food in lavish cafeterias. But new rules may curtail the popular practice. SAN FRANCISCO -- Food, glorious (and free) food, that classic tech company perk, may soon be off the menu here. Two city supervisors have introduced legislation that would nix the installation of non-retail cafeterias in office buildings, a measure aimed at encouraging legions of workers to patronize often struggling neighborhood eateries.

Coordination via predictive assistants from a game-theoretic view Machine Learning

We study machine learning-based assistants that support coordination between humans in congested facilities via congestion forecasts. In our theoretical analysis, we use game theory to study how an assistant's forecast that influences the outcome relates to Nash equilibria, and how they can be reached quickly in congestion game-like settings. Using information theory, we investigate approximations to given social choice functions under privacy constraints w.r.t. assistants. And we study dynamics and training for a specific exponential smoothing-based assistant via a linear dynamical systems and causal analysis. We report experiments conducted on a real congested cafeteria with about 400 daily customers where we evaluate this assistant and prediction baselines to gain further insight.

What a Visit to an AI-Enabled Hospital Might Look Like


The combination of machine learning, deep learning, natural language processing, and cognitive computing will soon change the ways that we interact with our environments. AI-driven smart services will sense what we're doing, know what our preferences are from our past behavior, and subtly guide us through our daily lives in ways that will feel truly seamless.

Can AI End Checkout Lines? NVIDIA Blog


Shopping in the future may feel a lot like shoplifting does today -- without the risk of getting nabbed -- if two artificial intelligence startups have their way. New Zealand's IMAGR and Silicon Valley's Mashgin aim to make checking out of grocery stores and company cafeterias a walk in the park. Many supermarkets offer self-checkout to save shoppers time. IMAGR founder William Chomley wants to skip the checkout altogether, so you can just walk right out the door. It's similar to the idea behind Amazon Go, being tested in a grocery store in downtown Seattle, which lets customers shop without ever stopping at a cashier on the way out.

A Prototype Mobile Expert System for Nutritional Diagnosis

AAAI Conferences

This paper describes NUTRITION UCR, a prototype expert system for human nutritional diagnosis developed in Java on Android using a service-oriented architecture. The system runs on mobile devices and offers smart features that evaluate the nutritional condition of an individual by assessing their physical characteristics and eating habits. We explain the knowledge engineering process used to develop the system, overview the system architecture and selected design tools, and summarize some preliminary results from the prototype implementation.