scholarly journals Using bacterial interaction and stereoscopic images for the location of obstacles on autonomous robots

2020 ◽  
Vol 9 (3) ◽  
pp. 906-913
Author(s):  
Fredy Martinez ◽  
Edwar Jacinto ◽  
Fernando Martínez
Keyword(s):  
Real Time ◽  
High Performance ◽  
Computational Cost ◽  
Cost Effective ◽  
Service Robots ◽  
Depth Information ◽  
Human Beings ◽  
Distance Information ◽  
Time Operation ◽  
Bacterial Interaction

Service robots are characterized by autonomously performing indoor tasks in unstructured environments, this condition of the environment prevents the prior programming of the map, which requires reactive behavior. These robots require real-time and cost-effective identification of obstacles in the environment, which includes not only distance information, but also depth information. This paper shows a strategy to estimate the position of obstacles in unknown environments. This strategy is characterized by low computational cost and real-time operation. The environments are selected because they are those usual to human beings, and this also influences our design, since we look for functional and morphological equivalence with human beings. This equivalence corresponds to the installation of two cameras in our robotic platform to form a stereoscopic system equivalent to the human. The images captured simultaneously are analyzed by a bacterial interaction scheme to define points on the obstacles. Our strategy showed a high performance in controlled environments. The scheme was able to establish distances to different points of the obstacle with 95% accuracy for distances between 0.8 and 2 m.

scholarly journals Obstacle detection for autonomous systems using stereoscopic images and bacterial behaviour

2020 ◽  
Vol 10 (2) ◽  
pp. 2164
Author(s):  
Fredy Martinez ◽  
Edwar Jacinto ◽  
Fernando Martinez
Keyword(s):  
Real Time ◽  
High Performance ◽  
Time Estimation ◽  
Obstacle Detection ◽  
Stereoscopic Vision ◽  
Human Interaction ◽  
Human Model ◽  
Service Robots ◽  
Indoor Environments ◽  
Time Operation

This paper presents a low cost strategy for real-time estimation of the position of obstacles in an unknown environment for autonomous robots. The strategy was intended for use in autonomous service robots, which navigate in unknown and dynamic indoor environments. In addition to human interaction, these environments are characterized by a design created for the human being, which is why our developments seek morphological and functional similarity equivalent to the human model. We use a pair of cameras on our robot to achieve a stereoscopic vision of the environment, and we analyze this information to determine the distance to obstacles using an algorithm that mimics bacterial behavior. The algorithm was evaluated on our robotic platform demonstrating high performance in the location of obstacles and real-time operation.

Real-Time Operation and Characterization of a High-Performance Time-Based Accelerometer

2015 ◽  
Vol 24 (6) ◽  
pp. 1703-1711 ◽  
Author(s):  
Rosana Alves Dias ◽  
Filipe Serra Alves ◽  
Margaret Costa ◽  
Helder Fonseca ◽  
Jorge Cabral ◽  
...  
Keyword(s):  
Real Time ◽  
High Performance ◽  
Performance Time ◽  
Time Operation ◽  
Real Time Operation

scholarly journals CONTROLLING AND MONITORING OF AUTOMATION WATER SUPPLY SYSTEM BASED ON IOT WITH THEFT IDENTIFICATION

2017 ◽  
Vol 5 (5) ◽  
pp. 320-325
Author(s):  
Ahmad T. Jaiad ◽  
Hamzah Sabr Ghayyib
Keyword(s):  
Water Supply ◽  
Real Time ◽  
Water Conservation ◽  
Water Distribution ◽  
Network Connectivity ◽  
Raspberry Pi ◽  
Human Beings ◽  
Residential Areas ◽  
Time Operation ◽  
Real Time Operation

Water is the most precious and valuable because it’s a basic need of all the human beings but, now a day water supply department are facing problem in real time operation this is because less amount of water in resources due to less rain fall. With increase in Population, urban residential areas have increased because of this reasons water has become a crucial problem which affects the problem of water distribution, interrupted water supply, water conservation, water consumption and also the water quality so, to overcome water supply related problems and make system efficient there is need of proper monitoring and controlling system. In this project, we are focusing on continuous and real time monitoring of water supply in IOT platform. Water supply with continuous monitoring makes a proper distribution so that, we can have a record of available amount of water in tanks, flow rate, abnormality in distribution line. Internet of things is nothing but the network of physical objects embedded with electronics, sensors, software, and network connectivity. Monitoring can be done from anywhere as central office. Using Adafruit as free sever data continuously pushed on cloud so we can see data in real time operation. Using different sensors with controller and raspberry pi as Mini computer can monitor data and also control operation from cloud with efficient client server communication.

scholarly journals Bayesian Localization in Real-Time using Probabilistic Maps and Unscented-Kalman-Filters

2021 ◽  
Author(s):  
Wael Farag ◽  
Keyword(s):  
Particle Filter ◽  
Real Time ◽  
High Performance ◽  
Unscented Kalman Filter ◽  
Spatial Clustering ◽  
Computational Cost ◽  
Measurement Data ◽  
High Definition ◽  
Probabilistic Maps ◽  
Reference Map

In this paper, based on the fusion of Lidar and Radar measurement data, high-definition probabilistic maps, and a tailored particle filter, a Real-Time Monte Carlo Localization (RT_MCL) method for autonomous cars is proposed. The lidar and radar devices are installed on the ego car, and a customized Unscented Kalman Filter (UKF) is used for their data fusion. Lidars are accurate in determining objects' positions and have a much higher spatial resolution. On the other hand, Radars are more accurate in measuring objects velocities and perform well in extreme weather conditions. Therefore, the merits of both sensors are combined using the UKF to provide pole-like static-objects pose estimations that are well suited to serve as landmarks for vehicle localization in urban environments. These pose estimations are then clustered using the Grid-Based Density-Based Spatial Clustering of Applications with Noise (GB-DBSCAN) algorithm to represent each pole landmarks in the form of a source-point model to reduce computational cost and memory requirements. A reference map that includes pole landmarks is generated off-line and extracted from a 3-D lidar to be used by a carefully designed Particle Filter (PF) for accurate ego-car localization. The particle filter is initialized by the combined GPS+IMU reading and used an ego-car motion model to predict the states of the particles. The data association between the estimated landmarks by the UKF and that in the reference map is performed using Iterative Closest Point (ICP) algorithm. The proposed pipeline is implemented using the high-performance language C++ and utilizes highly optimized math and optimization libraries for best real-time performance. Extensive simulation studies have been carried out to evaluate the performance of the RT_MCL in both longitudinal and lateral localization.

scholarly journals 3-D People Counting with a Stereo Camera on GPU Embedded Board

2018 ◽  
Vol 8 (11) ◽  
pp. 2017 ◽  
Author(s):  
Gyu-cheol Lee ◽  
Sang-ha Lee ◽  
Jisang Yoo
Keyword(s):  
Real Time ◽  
Stereo Matching ◽  
Depth Image ◽  
Depth Information ◽  
People Detection ◽  
Real Time Processing ◽  
Stereo Camera ◽  
People Counting ◽  
Time Operation ◽  
Real Time Operation

People counting in surveillance cameras is a key technology for understanding the flow population and generating heat maps. In recent years, people detection performance has been greatly improved with the development of object detection algorithms using deep learning. However, in places where people are crowded, the detection rate is low as people are often occluded by other people. We proposed a people-counting method using a stereo camera to resolve the non-detection problem due to the occlusion. We applied stereo matching to extract the depth image and convert the camera view to top view using depth information. People were detected using a height map and an occupancy map, and people were tracked and counted using a Kalman filter-based tracker. We operated the proposed method on the NVIDIA Jetson TX2 to check the real-time operation possibility on the embedded board. Experimental results showed that the proposed method had higher accuracy than the existing methods and that real-time processing is possible.

Using sequencing batch biofilm reactor (SBBR) to treat ABS wastewater

2000 ◽  
Vol 41 (4-5) ◽  
pp. 433-440 ◽  
Author(s):  
C.-N. Chang ◽  
H.R. Chen ◽  
C.H. Huang ◽  
A. Chao
Keyword(s):  
Real Time ◽  
Cost Effective ◽  
Optimal Growth ◽  
Fixed Time ◽  
Biofilm Reactor ◽  
Real Time Control ◽  
Time Control ◽  
Sequencing Batch Biofilm Reactor ◽  
Time Operation ◽  
Real Time Operation

Ratio of total Kjeldahl Nitrogen to COD for ABS (acrylnitrile, butadiene and styrene) wastewater is in a range of 0.12–0.17, which is significantly higher than that needed for optimal growth of an activated sludge. In this work, an automated Sequencing Batch Biofilm Reactor (SBBR) system at lab-scale is applied to reduce the amount of ABS; this system is controlled by an on-line monitoring of oxidation-reduction potential (ORP). A comparison of the operation efficiency for the lab-scale SBBR operated with the control of fix-time method and ORP-based real-time automatic method is presented. The results show that the system ORP can be used as an available parameter for achieving a real-time operation and control of the lab-scale SBBR. It is found that the reaction time is reduced of 11.1–55.2% if an ORP-based real-time control is used, instead of the fixed-time control. Also, the SBBR system is made more efficient and cost-effective.

scholarly journals A Lightweight Secure and Energy-Efficient Fog-Based Routing Protocol for Constraint Sensors Network

Energies ◽  
2020 ◽  
Vol 14 (1) ◽  
pp. 89
Author(s):  
Khalid Haseeb ◽  
Naveed Islam ◽  
Yasir Javed ◽  
Usman Tariq
Keyword(s):  
Real Time ◽  
Energy Efficient ◽  
High Performance ◽  
Cost Effective ◽  
Sensor Nodes ◽  
Time Data ◽  
Energy Efficient Routing ◽  
Routing Security ◽  
Simulation Based

The Wireless Sensor Network (WSN) has seen rapid growth in the development of real-time applications due to its ease of management and cost-effective attributes. However, the balance between optimization of network lifetime and load distribution between sensor nodes is a critical matter for the development of energy-efficient routing solutions. Recently, many solutions have been proposed for constraint-based networks using the cloud paradigm. However, they achieve network scalability with the additional cost of routing overheads and network latency. Moreover, the sensors’ data is transmitted towards application users over the uncertain medium, which leads to compromised data security and its integrity. Therefore, this work proposes a light-weight secure and energy-efficient fog-based routing (SEFR) protocol to minimize data latency and increase energy management. It exploits the Quality of Service (QoS) factors and facilitates time-sensitive applications with network edges. Moreover, the proposed protocol protects real-time data based on two levels of cryptographic security primitives. In the first level, a lightweight data confidentiality scheme is proposed between the cluster heads and fog nodes, and in the second level, a high-performance asymmetric encryption scheme is proposed among fog and cloud layers. The analysis of simulation-based experiments has proven the significant outcomes of the proposed protocol compared to existing solutions in terms of routing, security, and network management.

scholarly journals Electrolyzer Modeling and Real-Time Control for Optimized Production of Hydrogen Gas

2020 ◽  
Author(s):  
Benjamin Flamm ◽  
Christian Peter ◽  
Felix N. Büchi ◽  
John Lygeros
Keyword(s):  
Real Time ◽  
Nonlinear Models ◽  
Cost Effective ◽  
Hydrogen Gas ◽  
Real Time Control ◽  
Actual System ◽  
Thermal Dynamics ◽  
Time Operation ◽  
Effective Manner ◽  
Production Of Hydrogen

<pre>We present a method that operates an electrolyzer to meet the demand of a hydrogen refueling station in a cost-effective manner by solving a model-based optimal control problem. To formulate the underlying problem, we first conduct an experimental characterization of a Siemens SILYZER 100 polymer electrolyte membrane electrolyzer with \SI{100}{\kilo \watt} of rated power. We run experiments to determine the electrolyzer's conversion efficiency and thermal dynamics as well as the overload-limiting algorithm used in the electrolyzer. The resulting detailed nonlinear models are used to design a real-time optimal controller, which is then implemented on the actual system. Each minute, the controller solves a deterministic, receding-horizon problem which seeks to minimize the cost of satisfying a given hydrogen demand, while using a storage tank to take advantage of time-varying electricity prices and photovoltaic inflow. We illustrate in simulation the significant cost reduction achieved by our method compared to others in the literature, and then validate our method by demonstrating it in real-time operation on the actual system. </pre>

ECG-Based Biometrics

Biometrics ◽  
2017 ◽  
pp. 35-60
Author(s):  
Swanirbhar Majumder ◽  
Saurabh Pal
Keyword(s):  
Cloud Computing ◽  
Real Time ◽  
Human Heart ◽  
Cost Effective ◽  
Biometric Identification ◽  
Transform Domain ◽  
Human Beings ◽  
Biometric System ◽  
Real Time Identification ◽  
Cloud Servers

Like all human beings have different fingerprints, they have differently shaped hearts. The ECG, or the electrocardiogram, is the signature of the movements by the human heart, and thus, all ECGs are different. ECG biometrics is an area of biometric identification by the usage of the ECG features in time or frequency/transform domain. Along with these, if the present-day cloud servers also come to play, one has an efficient and cost-effective ECG-based biometric system using cloud computing to provide real-time identification via a secure connection. This chapter focuses on ECG-based biometrics with an overview at the end about how cloud-based big databases of stored ECG signatures and cloud servers can play a part in it.

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