scholarly journals Artificial Intelligence-Driven Autonomous Robot for Precision Agriculture

2021 ◽  
Vol 24 (1) ◽  
pp. 48-54
Author(s):  
Ivan Beloev ◽  
Diyana Kinaneva ◽  
Georgi Georgiev ◽  
Georgi Hristov ◽  
Plamen Zahariev
Keyword(s):  
Artificial Intelligence ◽  
Precision Agriculture ◽  
Communication Systems ◽  
Robotic Systems ◽  
Small Scale ◽  
Construction Process ◽  
End User ◽  
Agricultural Robots ◽  
Agricultural Enterprises ◽  
Human Labour

AbstractIn the recent years, robotic systems became more advanced and more accessible. This has led to their slow, but stable integration and use in different processes and applications, including in the agricultural domain. Nowadays, agricultural robots are developed with the aim to replace the human labour in the otherwise exhausting, time-consuming or dangerous activities. Agricultural robotic systems provide many advantages, which can differ based on the type of the robot and its sensors, actuators and communication systems. This paper presents the design, the construction process, the main characteristics and the evaluation of a prototype of a small-scale agricultural robot that can be used for some of the simplest activities in agricultural enterprises. The robot is designed as an end-user autonomous mobile system, which is capable of self-localization and can map or inspect a specific farming area. The decision-making capabilities of the robot are based on artificial intelligence (AI) algorithms, which allow it to perform specific actions in accordance to the situation and the surrounding environment. The presented prototype is in its early development and evaluation stages and the paper concludes with discussions on the possible further improvements of the platform.

scholarly journals Precision Vegetable Farming Technologies: An Update

2021 ◽  
Author(s):  
Prashant Kaushik
Keyword(s):  
Climate Change ◽  
Artificial Intelligence ◽  
Precision Agriculture ◽  
Economic Benefits ◽  
Geographical Information ◽  
Small Scale ◽  
Positioning System ◽  
Vegetable Crops ◽  
Vegetable Farming

The efficiency of precision vegetable farming cannot deny in the current of climate change. As compared to west adoption of reliability precision agriculture approaches in developing world is a gradual procedure. The small scale of farms limits economic benefits from currently accessible precision farming technologies. Nevertheless, horticulture interventions like geographical positioning system (GPS), geographical information system (GIS), artificial intelligence (AI), robotics, sensor technologies, etc., are being utilized for precision vegetable farming to improve production and quality of vegetables. This retains excellent promise for developing vegetable crops within the present farming scenario when climate change makes the whole rethink agriculture practices. Overall, this chapter will provide useful information about precision vegetable farming technologies for vegetable growers, enthusiasts, farmers, and researchers.

scholarly journals Expectations of artificial intelligence and the performativity of ethics: Implications for communication governance

2020 ◽  
Vol 7 (1) ◽  
pp. 205395172091593 ◽  
Author(s):  
Aphra Kerr ◽  
Marguerite Barry ◽  
John D Kelleher
Keyword(s):  
Artificial Intelligence ◽  
Communication Systems ◽  
Large Scale ◽  
The Public ◽  
Sociology Of Expectations ◽  
Public Expectations ◽  
Human Labour ◽  
Significant Divergence ◽  
Societal Expectations

This article draws on the sociology of expectations to examine the construction of expectations of ‘ethical AI’ and considers the implications of these expectations for communication governance. We first analyse a range of public documents to identify the key actors, mechanisms and issues which structure societal expectations around artificial intelligence (AI) and an emerging discourse on ethics. We then explore expectations of AI and ethics through a survey of members of the public. Finally, we discuss the implications of our findings for the role of AI in communication governance. We find that, despite societal expectations that we can design ethical AI, and public expectations that developers and governments should share responsibility for the outcomes of AI use, there is a significant divergence between these expectations and the ways in which AI technologies are currently used and governed in large scale communication systems. We conclude that discourses of ‘ethical AI’ are generically performative, but to become more effective we need to acknowledge the limitations of contemporary AI and the requirement for extensive human labour to meet the challenges of communication governance. An effective ethics of AI requires domain appropriate AI tools, updated professional practices, dignified places of work and robust regulatory and accountability frameworks.

scholarly journals Recognition of Bloom/Yield in Crop Images Using Deep Learning Models for Smart Agriculture: A Review

Agronomy ◽  
2021 ◽  
Vol 11 (4) ◽  
pp. 646
Author(s):  
Bini Darwin ◽  
Pamela Dharmaraj ◽  
Shajin Prince ◽  
Daniela Elena Popescu ◽  
Duraisamy Jude Hemanth
Keyword(s):  
Deep Learning ◽  
Crop Yield ◽  
Precision Agriculture ◽  
Soil Parameters ◽  
Learning Models ◽  
Weed Detection ◽  
Agricultural Industry ◽  
Agricultural Robots ◽  
Detection Techniques ◽  
Learning Techniques

Precision agriculture is a crucial way to achieve greater yields by utilizing the natural deposits in a diverse environment. The yield of a crop may vary from year to year depending on the variations in climate, soil parameters and fertilizers used. Automation in the agricultural industry moderates the usage of resources and can increase the quality of food in the post-pandemic world. Agricultural robots have been developed for crop seeding, monitoring, weed control, pest management and harvesting. Physical counting of fruitlets, flowers or fruits at various phases of growth is labour intensive as well as an expensive procedure for crop yield estimation. Remote sensing technologies offer accuracy and reliability in crop yield prediction and estimation. The automation in image analysis with computer vision and deep learning models provides precise field and yield maps. In this review, it has been observed that the application of deep learning techniques has provided a better accuracy for smart farming. The crops taken for the study are fruits such as grapes, apples, citrus, tomatoes and vegetables such as sugarcane, corn, soybean, cucumber, maize, wheat. The research works which are carried out in this research paper are available as products for applications such as robot harvesting, weed detection and pest infestation. The methods which made use of conventional deep learning techniques have provided an average accuracy of 92.51%. This paper elucidates the diverse automation approaches for crop yield detection techniques with virtual analysis and classifier approaches. Technical hitches in the deep learning techniques have progressed with limitations and future investigations are also surveyed. This work highlights the machine vision and deep learning models which need to be explored for improving automated precision farming expressly during this pandemic.

scholarly journals Millimeter Wave Spatial Channel Characterization for Vehicular Communications

Proceedings ◽  
2019 ◽  
Vol 42 (1) ◽  
pp. 64 ◽  
Author(s):  
Fidel Rodríguez-Corbo ◽  
Leyre Azpilicueta ◽  
Mikel Celaya-Echarri ◽  
Peio López-Iturri ◽  
Imanol Picallo ◽  
...  
Keyword(s):  
Millimeter Wave ◽  
Autonomous Vehicles ◽  
Communication Systems ◽  
Vehicular Networks ◽  
Small Scale ◽  
Vehicular Communications ◽  
Next Generation ◽  
Vehicular Communication ◽  
High Definition ◽  
High Data

With the growing demand of vehicle-mounted sensors over the last years, the amount of critical data communications has increased significantly. Developing applications such as autonomous vehicles, drones or real-time high-definition entertainment requires high data-rates in the order of multiple Gbps. In the next generation of vehicle-to-everything (V2X) networks, a wider bandwidth will be needed, as well as more precise localization capabilities and lower transmission latencies than current vehicular communication systems due to safety application requirements; 5G millimeter wave (mmWave) technology is envisioned to be the key factor in the development of this next generation of vehicular communications. However, the implementation of mmWave links arises with difficulties due to blocking effects between mmWave transceivers, as well as different channel impairments for these high frequency bands. In this work, the mmWave channel propagation characterization for V2X communications has been performed by means of a deterministic in-house 3D ray launching simulation technique. A complex heterogeneous urban scenario has been modeled to analyze the different propagation phenomena of multiple mmWave V2X links. Results for large and small-scale propagation effects are obtained for line-of-sight (LOS) and non-LOS (NLOS) trajectories, enabling inter-data vehicular comparison. These analyzed results and the proposed methodology can aid in an adequate design and implementation of next generation vehicular networks.

scholarly journals A Survey of Robots in Healthcare

Technologies ◽  
2021 ◽  
Vol 9 (1) ◽  
pp. 8 ◽  
Author(s):  
Maria Kyrarini ◽  
Fotios Lygerakis ◽  
Akilesh Rajavenkatanarayanan ◽  
Christos Sevastopoulos ◽  
Harish Ram Nambiappan ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
State Of The Art ◽  
The Elderly ◽  
Robotic Systems ◽  
Care Hospital ◽  
Robotic Technology ◽  
Persons With Disabilities ◽  
Survey Paper ◽  
Recent Advances ◽  
Art Research

In recent years, with the current advancements in Robotics and Artificial Intelligence (AI), robots have the potential to support the field of healthcare. Robotic systems are often introduced in the care of the elderly, children, and persons with disabilities, in hospitals, in rehabilitation and walking assistance, and other healthcare situations. In this survey paper, the recent advances in robotic technology applied in the healthcare domain are discussed. The paper provides detailed information about state-of-the-art research in care, hospital, assistive, rehabilitation, and walking assisting robots. The paper also discusses the open challenges healthcare robots face to be integrated into our society.

scholarly journals Modeling of Non-WSSUS Double-Rayleigh Fading Channels for Vehicular Communications

2017 ◽  
Vol 2017 ◽  
pp. 1-15 ◽  
Author(s):  
Carlos A. Gutiérrez ◽  
J. J. Jaime-Rodríguez ◽  
J. M. Luna-Rivera ◽  
Daniel U. Campos-Delgado ◽  
Javier Vázquez Castillo
Keyword(s):  
Fading Channels ◽  
Communication Systems ◽  
Rayleigh Fading ◽  
Channel Model ◽  
Closed Form Solution ◽  
Multipath Fading ◽  
Rayleigh Distribution ◽  
Rayleigh Fading Channels ◽  
Small Scale ◽  
Time Frequency

This paper deals with the modeling of nonstationary time-frequency (TF) dispersive multipath fading channels for vehicle-to-vehicle (V2V) communication systems. As a main contribution, the paper presents a novel geometry-based statistical channel model that facilitates the analysis of the nonstationarities of V2V fading channels arising at a small-scale level due to the time-varying nature of the propagation delays. This new geometrical channel model has been formulated following the principles of plane wave propagation (PWP) and assuming that the transmitted signal reaches the receiver antenna through double interactions with multiple interfering objects (IOs) randomly located in the propagation area. As a consequence of such interactions, the first-order statistics of the channel model’s envelope are shown to follow a worse-than-Rayleigh distribution; specifically, they follow a double-Rayleigh distribution. General expressions are derived for the envelope and phase distributions, four-dimensional (4D) TF correlation function (TF-CF), and TF-dependent delay and Doppler profiles of the proposed channel model. Such expressions are valid regardless of the underlying geometry of the propagation area. Furthermore, a closed-form solution of the 4D TF-CF is presented for the particular case of the geometrical two-ring scattering model. The obtained results provide new theoretical insights into the correlation and spectral properties of small-scale nonstationary V2V double-Rayleigh fading channels.

Effects of Deep Learning Technologies on Employment in the Field of Digital Communication Systems

2021 ◽  
Vol 12 (4) ◽  
pp. 35-42
Author(s):  
Thomas Alan Woolman ◽  
Philip Lee
Keyword(s):  
Artificial Intelligence ◽  
Deep Learning ◽  
Communication Systems ◽  
Digital Communication ◽  
The United States ◽  
Learning Technologies ◽  
Technological Unemployment ◽  
Current State ◽  
Challenges And Opportunities ◽  
Digital Communication Systems

There are significant challenges and opportunities facing the economies of the United States in the coming decades of the 21st century that are being driven by elements of technological unemployment. Deep learning systems, an advanced form of machine learning that is often referred to as artificial intelligence, is presently reshaping many aspects of traditional digital communication technology employment, primarily network system administration and network security system design and maintenance. This paper provides an overview of the current state-of-the-art developments associated with deep learning and artificial intelligence and the ongoing revolutions that this technology is having not only on the field of digital communication systems but also related technology fields. This paper will also explore issues and concerns related to past technological unemployment challenges, as well as opportunities that may be present as a result of these ongoing technological upheavals.

End-User-Driven Approach for Regulatory Compliance in the Public Cloud

2021 ◽  
Vol 12 (3) ◽  
pp. 1-19
Author(s):  
Jitendra Singh ◽  
Vikas Kumar
Keyword(s):  
Present State ◽  
Business Groups ◽  
Regulatory Compliance ◽  
Third Party ◽  
Expert Advice ◽  
Small Scale ◽  
Public Cloud ◽  
End User ◽  
The Public ◽  
Limited Budget

Regulatory compliance is equally binding on small and medium business groups. Owing to the small scale and limited budget, such SMBs are unable to seek expert advice. To adequately guard the SMBs in regulatory compliance, the present work proposed a third-party managed-end user-driven approach that renders the list of regulatory acts applicable in one's case according to the country of one's residence, services subscribed, and type of the operations to be carried out in subscribed cloud paradigm. The list of applicable regulatory acts are rendered at the subscriber's end only. In addition, the proposed method notifies the present state of compliance of under-considered cloud providers. Based on the recommendation received, the subscriber can proceed with his decision to subscribe or not to subscribe in the event if desired compliances do not exist. This technological assistance will eliminate the need to possess the required knowledge in regulatory acts or seeking advice from the regulatory expert.

COMPARATIVE TECHNICAL AND ECONOMIC ESTIMATION OF THE SMALL-SCALE ON-FARM COMPOUND FEED PLANTS

2021 ◽  
pp. 59-65
Author(s):  
SERGEY V. BRAGINETS ◽  
Keyword(s):  
Net Present Value ◽  
Raw Materials ◽  
Farm Animals ◽  
Small Scale ◽  
Hammer Mill ◽  
Capital Investments ◽  
Agricultural Enterprises ◽  
Feed Production ◽  
Effi Ciency ◽  
On Farm

On-farm compound feed production from self-produced raw materials is favorable to agricultural enterprises under present-day conditions. The authors carried out a comparative technical and economic study of the conventional and modular small-scale on-farm compound feed plants with a capacity of 2 tons per hour, designed for agricultural enterprises with an average livestock population of 6…8 thousand pigs. The proposed modular plant consists of two modules – the operative storage of raw materials and the main module of grinding and mixing. Modules with installed equipment are delivered and placed on a light foundation, connected by transport equipment and with tanks for raw materials and fi nished products. The conventional factory is a technological line housed in a hangar and used for crushing, metering, and mixing raw materials. It consists of a separator, a hammer mill, weighing equipment, a mixer, containers for raw materials and fi nished products, transport, and aspiration equipment. The technical and economic analysis has shown that the erection and operation of the on-farm modular enterprise require 41% less capital investments than a traditional compound feed plant of the same capacity. The use of a small-scale modular plant will reduce operating costs by 23.8% (from 3094 to 2358 thousand rubles), increase the specifi c economic eff ect from the compound feed production by 1.6% (from 8.64 to 8.78 thousand rubles per ton) and return on margin by 4% (from 10.2 to 10.6%), reduce the payback period by 42% (from 0.8 to 0.46 years), and increase the net present value by 3% (from 66167 to 68216 thousand rubles), as compared to a conventional enterprise. The modular on-farm plants producing loose compound feed with a productivity of up to 3 tons per hour are profi table and economically sound as they can increase production effi ciency of compound feeds for farm animals.`

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