scholarly journals Smart Warehouse Governance using AI and Raspberry Pi

2020 ◽  
Vol 9 (3) ◽  
pp. 176-179
Keyword(s):  
Artificial Intelligence ◽  
Large Scale ◽  
Raspberry Pi ◽  
Sorting Algorithm ◽  
Frame Size ◽  
Sorting Technique ◽  
Pick And Place ◽  
Automated Warehouses ◽  
Labor Requirements ◽  
Five Axis

Sorting is the process of systematic selection and arrangement. Sorting involves intense labor work. The use of Artificial Intelligence in recognizing the objects by their color makes the process of sorting completely autonomous. Modern Industries require modern solutions for the problems encountered during the process of sorting. With the advent of Artificial Intelligence, the machines that can recognize an object by their color proves to be a primary solution that can completely automate the process of sorting. This paper presents a five-axis arm mounted on a robotic model that makes use of a color sorting technique. It performs pick and place operations in realtime. The color sorting technique detects the color of the object in the frame captured by the camera. The frame size is used to detect the position of the object in the real world. The robot model moves according to the frame size of the object. Raspberry Pi microcontroller drives the servo motor and dc motor to move the five-axis arm and the robotic model to sort and perform pick and place operation based on their color. The color sorting algorithm is based on the Hue-Saturation-Value model. This model finds its application in places where sorting is done based on color and not the object itself. For example, it is used to sort objects like different colored clothes, food items, etc. It also finds its application in very large scale warehouses such as Amazon, Flipkart, etc which focusses on smart automated warehouses that reduce the labor requirements

scholarly journals BattleNet: Capturing Advantageous Battlefield in RTS Games (Student Abstract)

2020 ◽  
Vol 34 (10) ◽  
pp. 13849-13850
Author(s):  
Donghyeon Lee ◽  
Man-Je Kim ◽  
Chang Wook Ahn
Keyword(s):  
Artificial Intelligence ◽  
Decision Making ◽  
Real Time ◽  
Large Scale ◽  
Outcome Predictor ◽  
Short Term ◽  
Rts Game

In a real-time strategy (RTS) game, StarCraft II, players need to know the consequences before making a decision in combat. We propose a combat outcome predictor which utilizes terrain information as well as squad information. For training the model, we generated a StarCraft II combat dataset by simulating diverse and large-scale combat situations. The overall accuracy of our model was 89.7%. Our predictor can be integrated into the artificial intelligence agent for RTS games as a short-term decision-making module.

Recognition of teaching method effects based on grid model simplification and artificial intelligence

2020 ◽  
pp. 1-11
Author(s):  
Guo Yunfeng ◽  
Li Jing
Keyword(s):  
Artificial Intelligence ◽  
Teaching Method ◽  
Evaluation Model ◽  
Geometric Constraints ◽  
Sorting Algorithm ◽  
Grid Model ◽  
Model Based ◽  
Refinement Method ◽  
Method Effects ◽  
Structure Simplification

In order to improve the effect of the teaching method evaluation model, based on the grid model, this paper constructs an artificial intelligence model based on the grid model. Moreover, this paper proposes a hexahedral grid structure simplification method based on weighted sorting, which comprehensively sorts the elimination order of candidate base complexes in the grid with three sets of sorting items of width, deformation and price improvement. At the same time, for the elimination order of basic complex strings, this paper also proposes a corresponding priority sorting algorithm. In addition, this paper proposes a smoothing regularization method based on the local parameterization method of the improved SLIM algorithm, which uses the regularized unit as the reference unit in the local mapping in the SLIM algorithm. Furthermore, this paper proposes an adaptive refinement method that maintains the uniformity of the grid and reduces the surface error, which can better slow down the occurrence of geometric constraints caused by insufficient number of elements in the process of grid simplification. Finally, this paper designs experiments to study the performance of the model. The research results show that the model constructed in this paper is effective.

New Harvesting and Curing Techniques in the Production of Breeder's Seed Peanuts1

1979 ◽  
Vol 6 (2) ◽  
pp. 70-72
Author(s):  
T. A. Coffelt ◽  
F. S. Wright ◽  
J. L. Steele
Keyword(s):  
Large Scale ◽  
Combine Method ◽  
Frost Damage ◽  
New Method ◽  
Experimental Equipment ◽  
Harvesting Method ◽  
Curing Methods ◽  
Labor Requirements ◽  
High Level ◽  
Varietal Purity

Abstract A new method of harvesting and curing breeder's seed peanuts in Virginia was initiated that would 1) reduce the labor requirements, 2) maintain a high level of germination, 3) maintain varietal purity at 100%, and 4) reduce the risk of frost damage. Three possible harvesting and curing methods were studied. The traditional stack-pole method satisfied the latter 3 objectives, but not the first. The windrow-combine method satisfied the first 2 objectives, but not the last 2. The direct harvesting method satisfied all four objectives. The experimental equipment and curing procedures for direct harvesting had been developed but not tested on a large scale for seed harvesting. This method has been used in Virginia to produce breeder's seed of 3 peanut varieties (Florigiant, VA 72R and VA 61R) during five years. Compared to the stackpole method, labor requirements have been reduced, satisfactory levels of germination and varietal purity have been obtained, and the risk of frost damage has been minimized.

Prospects for Cooperation Between Russia and the Republic of Korea in the Fields of Big Data, Network and Artificial Intelligence for the Development of the Digital Economy

2021 ◽  
Vol 65 (8) ◽  
pp. 51-60
Author(s):  
Yujeong Kim
Keyword(s):  
Artificial Intelligence ◽  
Big Data ◽  
Large Scale ◽  
Technology Development ◽  
Technological Development ◽  
Digital Economy ◽  
Republic Of Korea ◽  
Data Network ◽  
Leading Position ◽  
The Government

Today, each country has interest in digital economy and has established and implemented policies aimed at digital technology development and digital transformation for the transition to the digital economy. In particular, interest in digital technologies such as big data, 5G, and artificial intelligence, which are recognized as important factors in the digital economy, has been increasing recently, and it is a time when the role of the government for technological development and international cooperation becomes important. In addition to the overall digital economic policy, the Russian and Korean governments are also trying to improve their international competitiveness and take a leading position in the new economic order by establishing related technical and industrial policies. Moreover, Republic of Korea often refers to data, network and artificial intelligence as D∙N∙A, and has established policies in each of these areas in 2019. Russia is also establishing and implementing policies in the same field in 2019. Therefore, it is timely to find ways to expand cooperation between Russia and Republic of Korea. In particular, the years of 2020and 2021marks the 30th anniversary of diplomatic relations between the two countries, and not only large-scale events and exchange programs have prepared, but the relationship is deepening as part of the continued foreign policy of both countries – Russia’s Eastern Policy and New Northern Policy of Republic of Korea. Therefore, this paper compares and analyzes the policies of the two countries in big data, 5G, and artificial intelligence to seek long-term sustainable cooperation in the digital economy.

scholarly journals COVID-19 Authorized Entry with Face Mask Detection using Raspberry Pi

2021 ◽  
Vol 9 (VI) ◽  
pp. 1862-1867
Author(s):  
Anju Ajay
Keyword(s):  
Large Scale ◽  
Facial Recognition ◽  
Face Mask ◽  
Raspberry Pi ◽  
Wireless Internet ◽  
Great Demand ◽  
Embedded Device ◽  
Internet Connection ◽  
Battery Power ◽  
Python Programming

There are no effective face mask detection applications in the current COVID-19 scenario, which is in great demand for transportation, densely populated places, residential districts, large-scale manufacturers, and other organizations to ensure safety. In addition, the lack of big datasets of photographs with mask has made this task more difficult. With the use of Python programming, the Open CV library, Keras, and tensor flow, this project presents a way for recognizing persons without wearing a face mask using the facial recognition methodology. This is a self-contained embedded device that was created with the Raspberry Pi Electronic Development Board and runs on battery power. We make use of a wireless internet connection using USB modem. In comparison to other existing systems, our proposed method is more effective, reliable, and consumes significantly less data and electricity

scholarly journals Artificial Intelligence and the Transformation of Humans, Law and Technology Interactions in Judicial Proceedings

2020 ◽  
Vol 2 (1) ◽  
pp. 4-18 ◽  
Author(s):  
Francesco Contini
Keyword(s):  
Artificial Intelligence ◽  
Large Scale ◽  
Technology Development ◽  
Actor Network Theory ◽  
Digital Environment ◽  
Law And Technology ◽  
Administration Of Justice ◽  
Case Comparison ◽  
Judicial Proceedings ◽  
Online Forms

The paper connects the potentially disruptive effects of Artificial Intelligence (AI) deployment in the administration of justice to the pre-existing trajectories and consequences of court technology development. The theoretical framework combines Luhmann’s theory of technology with actor–network theory to analyse how the new digital environment affects judicial agency. Then, it explores law and technology dynamics to map out the conditions that make legal the use of technologies in judicial proceedings. The framework is applied to analyse ‘traditional’ digital technologies (simple online forms and large-scale e-justice platforms) and AI-based systems (speech-to-text and recidivism assessment). The case comparison shows similarities and dynamics triggered by AI and traditional technologies, as well as a radical difference. While system developers and owners remain accountable before the law for the functioning of traditional systems, with AI, such accountability is transferred to users. Judges—users in general—remain accountable for the consequences of their actions supported or suggested by systems that are opaque and autonomous. This contingency, if not adequately faced with new forms of accountability, restricts the areas in which AI can be used without hampering judicial integrity.

scholarly journals Application Problems and Solutions of Intelligent Airport Service Robots

2020 ◽  
Vol 198 ◽  
pp. 04030
Author(s):  
Dai Yanyan ◽  
Chen Meng
Keyword(s):  
Artificial Intelligence ◽  
Cloud Computing ◽  
Big Data ◽  
Large Scale ◽  
New Technologies ◽  
Effective Means ◽  
Third Party ◽  
Service Robots ◽  
Service Robot ◽  
Operation Conditions

With the development of new technologies such as artificial intelligence, big data, and cloud computing, the “intelligent airport” is considered to be an effective means to solve or alleviate the current industry problems such as large-scale airport business, the large number of operating entities, and the complicated operation conditions. This paper is about the collaboration between universities and enterprises based on the concept of service design. Relying on big data and cloud computing technology, this paper addresses the problems of airport service robots in inquiries, blind spots of security inspection, and full monomer smart navigation diffluence, combined with the basic technology of service robot artificial intelligence and the third-party interface to design solutions to effectively solve the problems of process.

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