AI bots in the agriculture field can harvest crops at a higher volume and faster pace than human laborers. By leveraging computer vision helps to monitor the weed and spray them. Thus, Artificial Intelligence is helping farmers find more efficient ways to protect their crops from weeds.
Agriculture may be a major business and therefore the foundation of the economy. In 2016, the calculable worth additional by the agriculture business was calculable at but one percent people GDP. The U.S. Environmental Protection Agency (EPA) estimates that agriculture contributes regarding $ 330 billion annually to the economy.
Artificial Intelligence In Agriculture & Its Status in IndiaJanhviTripathi
Worldwide, agriculture is a $5 trillion industry, and with the ever increasing population, the world will need to produce 50% more food by 2050 which cannot be accomplished with the percentage of land under cultivation. Factors such as climate change, population growth and food security concerns have propelled the industry into seeking more innovative approaches to protecting and improving crop yield. As a result, Artificial Intelligence is steadily emerging as part of the industry’s technological evolution which help can help farmers get more from the land while using resources more sustainably, yielding healthier crops, control pests, monitor soil, help with workload, etc
*All the media belongs to the respective owners*
Contact me for further queries & discussions...
A confluence of factors have converged to afford the opportunity to apply data science at large scale to agricultural production. The demand for agricultural outputs is growing and there is a need to meet this demand by utilizing increasingly mechanized precision agriculture and enormous data volumes collected to intelligently optimize agriculture outputs. We will consider the machine learning challenges related to optimizing global food production.
AI bots in the agriculture field can harvest crops at a higher volume and faster pace than human laborers. By leveraging computer vision helps to monitor the weed and spray them. Thus, Artificial Intelligence is helping farmers find more efficient ways to protect their crops from weeds.
Agriculture may be a major business and therefore the foundation of the economy. In 2016, the calculable worth additional by the agriculture business was calculable at but one percent people GDP. The U.S. Environmental Protection Agency (EPA) estimates that agriculture contributes regarding $ 330 billion annually to the economy.
Artificial Intelligence In Agriculture & Its Status in IndiaJanhviTripathi
Worldwide, agriculture is a $5 trillion industry, and with the ever increasing population, the world will need to produce 50% more food by 2050 which cannot be accomplished with the percentage of land under cultivation. Factors such as climate change, population growth and food security concerns have propelled the industry into seeking more innovative approaches to protecting and improving crop yield. As a result, Artificial Intelligence is steadily emerging as part of the industry’s technological evolution which help can help farmers get more from the land while using resources more sustainably, yielding healthier crops, control pests, monitor soil, help with workload, etc
*All the media belongs to the respective owners*
Contact me for further queries & discussions...
A confluence of factors have converged to afford the opportunity to apply data science at large scale to agricultural production. The demand for agricultural outputs is growing and there is a need to meet this demand by utilizing increasingly mechanized precision agriculture and enormous data volumes collected to intelligently optimize agriculture outputs. We will consider the machine learning challenges related to optimizing global food production.
Both climate change and global food demand are expected to become more severe in the upcoming decades. In terms of consistently growing population, the agricultural industry will need to embrace better methods to feed our people with a sufficient and healthy supply of food. The Internet of Things technology (IoT) is a breakthrough technology system that evolved from the convergence of wireless technologies and the Internet. Machine-to-machine (M2M) communication systems will be embedded in an objects’ manufacture and will operate automatically without human-to-computer interaction. This will allow information to be transmitted among wireless devices amongst the machines themselves. With IoT innovation, farmers and growers will be able to boost productivity, strengthen pest control and reduce possible energy waste during cultivation.
PROBLEM:
Smart farming is a new concept in the field of agriculture with its complex mechanisms, fresh-coined terms, usage statistics and analytics, and its implementations differ from country to country. There is a shortage of structured information on this, especially, analytical research on comparison the countries’ past and current performance and future-expected gains on the field.
OBJECTIVES:
This paper’s mission is to familiarize the students with the mechanisms, terms, statistics, analytical research data and to do the comparison of the different scenarios of Smart Farming’s implementation in Germany and Uzbekistan.
APPROACHES:
Introducing interconnected technology fields that smart farming strongly related to:
- Farm Management Information Systems
- Precision Agriculture
- Agricultural automation and robotics
Comparing the current and future expected state of the SMART FARMING technology in Uzbekistan and Germany.
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
An agricultural robot is a robot deployed for agricultural purposes. Emerging applications of robots or drones in agriculture include weed control, cloud seeding, planting seeds, harvesting, environmental monitoring, and soil analysis.
Agricultural robots automate slow, repetitive, and dull tasks for farmers, allowing them to focus more on improving overall production yields. Some of the most common robots in agriculture are used for: Harvesting and picking
APPLICATION OF INFORMATION AND COMMUNICATION TOOLS (ICTs) IN MODERN AGRICULTURESREENIVASAREDDY KADAPA
ICT can deliver fast, reliable, and accurate information in a user-friendly manner for practical utilization by the end-user. ICT includes any communication device or application encompassing radio, television, cellular phones, computer and network hardware and software, satellite systems, and as well as the various services and applications associated with them, such as videoconferencing and digital learning.
How are drones used for farming? The use of drones in agriculture is the future. Heavy lift drones capable of crop dusting and drones equipped with multispectral sensors will change the way in which farming is done.
Presentation for a group of employees of Centric, a large software consultancy company. It provides an illustration of how IoT is currently being developed in farming, agri-logistics and food consumption. It also addresses the technical and organizational challenges that have to be overcome to make IoT application in agri-food a success. Open platforms and software development and above all appropriate business models are key issues that have to be addressed. The new EU-project "Internet of Food and Farm 2020" will address these issues by fostering a collaborative IoT ecosystem to upscale the use of IoT in agri-food.
Basic knowledge of application of computers in agriculturejatinder pal singh
Computer use among agro-meteorologists, agronomists and other agricultural professionals has risen rapidly in the past decade.
The application of the computer in agriculture research originally exploited for the conversion of statistical formula or complex model in digital farm for easy and accurate calculation which are found relatively tedious in the manual calculation.
The use of technology and artificial intelligence in agriculture is more common every day. In Summar Financial we focus our efforts on helping the United States leading companies to expand the market. Join us and ask for our finance programs!
Systems of IoT Systems for Smart Food and FarmingCor Verdouw
This presentation introduces a Systems of Systems approach to deal with the huge heterogeneity of IoT architectures in the food and agri domain. More specifically, it analyses the main commonalities and synergies of the IoF2020 use cases and proposes an architectural approach in which autonomous IoT systems function as interoperable nodes in a software ecosystem.
Both climate change and global food demand are expected to become more severe in the upcoming decades. In terms of consistently growing population, the agricultural industry will need to embrace better methods to feed our people with a sufficient and healthy supply of food. The Internet of Things technology (IoT) is a breakthrough technology system that evolved from the convergence of wireless technologies and the Internet. Machine-to-machine (M2M) communication systems will be embedded in an objects’ manufacture and will operate automatically without human-to-computer interaction. This will allow information to be transmitted among wireless devices amongst the machines themselves. With IoT innovation, farmers and growers will be able to boost productivity, strengthen pest control and reduce possible energy waste during cultivation.
PROBLEM:
Smart farming is a new concept in the field of agriculture with its complex mechanisms, fresh-coined terms, usage statistics and analytics, and its implementations differ from country to country. There is a shortage of structured information on this, especially, analytical research on comparison the countries’ past and current performance and future-expected gains on the field.
OBJECTIVES:
This paper’s mission is to familiarize the students with the mechanisms, terms, statistics, analytical research data and to do the comparison of the different scenarios of Smart Farming’s implementation in Germany and Uzbekistan.
APPROACHES:
Introducing interconnected technology fields that smart farming strongly related to:
- Farm Management Information Systems
- Precision Agriculture
- Agricultural automation and robotics
Comparing the current and future expected state of the SMART FARMING technology in Uzbekistan and Germany.
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
An agricultural robot is a robot deployed for agricultural purposes. Emerging applications of robots or drones in agriculture include weed control, cloud seeding, planting seeds, harvesting, environmental monitoring, and soil analysis.
Agricultural robots automate slow, repetitive, and dull tasks for farmers, allowing them to focus more on improving overall production yields. Some of the most common robots in agriculture are used for: Harvesting and picking
APPLICATION OF INFORMATION AND COMMUNICATION TOOLS (ICTs) IN MODERN AGRICULTURESREENIVASAREDDY KADAPA
ICT can deliver fast, reliable, and accurate information in a user-friendly manner for practical utilization by the end-user. ICT includes any communication device or application encompassing radio, television, cellular phones, computer and network hardware and software, satellite systems, and as well as the various services and applications associated with them, such as videoconferencing and digital learning.
How are drones used for farming? The use of drones in agriculture is the future. Heavy lift drones capable of crop dusting and drones equipped with multispectral sensors will change the way in which farming is done.
Presentation for a group of employees of Centric, a large software consultancy company. It provides an illustration of how IoT is currently being developed in farming, agri-logistics and food consumption. It also addresses the technical and organizational challenges that have to be overcome to make IoT application in agri-food a success. Open platforms and software development and above all appropriate business models are key issues that have to be addressed. The new EU-project "Internet of Food and Farm 2020" will address these issues by fostering a collaborative IoT ecosystem to upscale the use of IoT in agri-food.
Basic knowledge of application of computers in agriculturejatinder pal singh
Computer use among agro-meteorologists, agronomists and other agricultural professionals has risen rapidly in the past decade.
The application of the computer in agriculture research originally exploited for the conversion of statistical formula or complex model in digital farm for easy and accurate calculation which are found relatively tedious in the manual calculation.
The use of technology and artificial intelligence in agriculture is more common every day. In Summar Financial we focus our efforts on helping the United States leading companies to expand the market. Join us and ask for our finance programs!
Systems of IoT Systems for Smart Food and FarmingCor Verdouw
This presentation introduces a Systems of Systems approach to deal with the huge heterogeneity of IoT architectures in the food and agri domain. More specifically, it analyses the main commonalities and synergies of the IoF2020 use cases and proposes an architectural approach in which autonomous IoT systems function as interoperable nodes in a software ecosystem.
Wireless Sensor Networks UNIT-1
You can watch my lectures at:
Digital electronics playlist in my youtube channel:
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My Website : https://easyninspire.blogspot.com/
Comparative Performance Analysis of Wireless Communication Protocols for Inte...chokrio
The systems based on intelligent sensors are currently expanding, due to theirs functions and theirs performances of intelligence: transmitting and receiving data in real-time, computation and processing algorithms, metrology remote, diagnostics, automation and storage measurements…The radio frequency wireless communication with its multitude offers a better solution for data traffic in this kind of systems. The mains objectives of this paper is to present a solution of the problem related to the selection criteria of a better wireless communication technology face up to the constraints imposed by the intended application and the evaluation of its key features. The comparison between the different wireless technologies (Wi-Fi, Wi-Max, UWB, Bluetooth, ZigBee, ZigBeeIP, GSM/GPRS) focuses on their performance which depends on the areas of utilization. Furthermore, it shows the limits of their characteristics. Study findings can be used by the developers/ engineers to deduce the optimal mode to integrate and to operate a system that guarantees quality of communication, minimizing energy consumption, reducing the implementation cost and avoiding time constraints.
Complete report on DATA ACQUISITION SCHEME IN WIRELESS SENSOR NETWORKRutvik Pensionwar
With the development in data acquisition system, information-collection plays an increasingly important role in the field of Wireless Technology. There has been tremendous increase in the use of sensors in each and every field. In order to get fast response from these sensors the delay should be reduced. Also the congestion in the network should be tackled to increase the efficiency. Wireless Sensor Networks (WSNs) consist of many tiny wireless sensors which operate in an environment in order to collect data. In a typical WSN, data is gathered from environment by sensor nodes and then transmitted to a base station. All these operations are executed by sensor nodes with keeping in mind the limitation of power. Reliable communication, power efficiency, network congestion issues are among major concerns. So in our project our main focus is to avoid the packet loss by increasing the network efficiency and handling the congestion in the network by proper buffer management. Finally visualization of processed data is done at the base station and the future enhancement could be to directly send the sensed data to cloud storage.
Abstract: Wearable sensors that measure limb movements posture, and physiological conditions can yield high resolution quantitative data .It can be used to better understand the disease and develop more effective treatments. In existing, classification algorithm is used to extract the feature from sensor, so these feature selection may lead to rapid battery depletion due to the absence of computing complexity. The notion of power aware feature selection is proposed which aims at minimizing energy consumption also it considers the energy cost of individual features that are calculated in real time. A graph model is introduced to represent correlation and computing complexity of the features. The problem is formulated using integer programming and a greedy approximation is presented to select the features in a power efficient manner. Experimental results on thirty channels of activity data collected from real subjects demonstrate that an approach can significantly reduce energy consumption of the computing module, resulting in more than 30 percent energy savings while achieving 96.7 percent classification accuracy.
A Review of Efficient Information Delivery and Clustering for Drip Irrigation Management using WSN.1
S. R. Boselin Prabhu, Dr. S. Sophia and A. Inigo Mathew
Dual Hybrid Algorithm for Job Shop Scheduling Problem ........................................................................ 14
Do Tuan Hanh, Vu Dinh Hoa and Nguyen Huu Mui
CThe Comparative Analysis of Power Optimization in Clustered Sleep Transistors................................ 25
M. Divya Sree, Y. Kranthi Kiran and Vijaya Vardhan Kancharla
Cyber Crimes Incidents in Financial Institutions of Tanzania ................................................................... 37
Edison Wazoel Lubua (PhD)
Design Issues and Applications of Wireless Sensor Networkijtsrd
Efficient design and implementation of wireless sensor networks has become a hot area of research in recent years, due to the vast potential of sensor networks to enable applications that connect the physical world to the virtual world. By networking large numbers of tiny sensor nodes, it is possible to obtain data about physical phenomena that was difficult or impossible to obtain in more conventional ways. In future as advances in micro-fabrication technology allow the cost of manufacturing sensor nodes to continue to drop, increasing deployments of wireless sensor networks are expected, with the networks eventually growing to large numbers of nodes.Potential applications for such large-scale wireless sensor networks exist in a variety of fields, including medical monitoring, environmental monitoring, surveillance, home security, military operations, and industrial machine monitoring etc. G. Swarnalatha | R. Srilalitha"Design Issues and Applications of Wireless Sensor Network" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-1 | Issue-6 , October 2017, URL: http://www.ijtsrd.com/papers/ijtsrd4688.pdf http://www.ijtsrd.com/engineering/computer-engineering/4688/design-issues-and-applications-of-wireless-sensor-network/g-swarnalatha
An overview of how Wireless Sensor Networks are being extended to a system which has tremendous capabilities. The future is all about Smart Dust. Trillions of sensors may be planted across the world to improve the ecosystem as well as the lives of human beings. Although the aim of reducing the volume to orders of micrometer has not yet been fulfilled, considerable developments have been made to build motes that combine sensing, computing, wireless communication capabilities and autonomous power supply within volume of only few millimeters and that too at low cost.
Development in the technology of sensor such as Micro Electro Mechanical Systems (MEMS), wireless communications, embedded systems, distributed processing and wireless sensor applications have contributed a large transformation in Wireless
Sensor Network (WSN) recently. It assists and improves work performance both in the field of industry and our daily life. Wireless Sensor Network has been widely used in many areas especially for surveillance and monitoring in agriculture and habitat monitoring. Environment monitoring has become an important field of control and protection, providing real-time system and control communication
with the physical world. An intelligent and smart Wireless Sensor Network system can gather and process a large amount of data from the beginning of the monitoring and manage air quality, the conditions of traffic, to weather situations.
Precision Agriculture Based on Wireless Sensor NetworkIJLT EMAS
Satellite farming or precision agriculture is a concept
based on measurement, observations and response to the inter
and intra farm variations in the crops. The growth and
advancements in wireless sensor network (WSN) technology has
directed agriculture sector into a new trend of smart agriculture.
WSN technology provides processing of real time data from field.
This is obtained through the sensors which are physically
deployed into the fields. These smart agriculture approaches by
the help of WSN reduces wastage of resources in farming unlike
the conventional practice, and contribute in effectively utilizing
the necessary resources resulting in increased crop yields. In this
paper wireless agriculture and environment sensing system for
crop monitoring is presented. The system test is implemented
using the real time agricultural data and from the historical data.
The system precisely acquires data and the information from the
environment.
Abstract A wireless sensor network (WSN) consists of sensors which are densely distributed to monitor physical or environmental conditions, such as temperature, sound, pressure, etc. The sensor data is transmitted to network coordinator which is heart of the wireless personal area network. In the modern scenario wireless networks contains sensors as well as actuators. ZigBee is newly developed technology that works on IEEE standard 802.15.4, which can be used in the wireless sensor network (WSN). The low data rates, low power consumption, low cost are main features of ZigBee. WSN is composed of ZigBee coordinator (network coordinator), ZigBee router and ZigBee end device. The sensor nodes information in the network will be sent to the coordinator, the coordinator collects sensor data, stores the data in memory, process the data, and route the data to appropriate node. Index Terms: WSN, ZigBee.
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology.
Precision Farming (PF) is introduced and history in short is reviewed. Essential activities of GPS locating, soil mapping, GIS dataprocessing and presentation and VRT application are described. Basic principles of PF are shown to be:
• Precision Farming is the management process of within-field variability.
• This management must bring profit or at least reduce the risk of loss
• This management must reduce the impact of farming on environment.
Techniques used in Precision Farming are described. Economics of Precision Farming is discussed. A general cost/benefit analysis and profitability of PF are reviewed. The price of PF adoption facing a farmer is discussed. Methods of process analysis and activity based costing are shown as useful instruments for PF process analysis and model building. PF process is analysed and process graph is developed.
The “Club of Ossiach”, a group of agriculturists, agribusiness managers, agriculture technologists and agricultural ICT specialists from around the world, met at Ossiach between 17-19 June 2013 at the “AgriFuture Days” Conference. They reviewed current trends and
possible discontinuities resulting from political, social, environmental and technological changes, potentially impacting on the future of agriculture, farming, rural viability, food and nutrition worldwide.
LF Energy Webinar: Electrical Grid Modelling and Simulation Through PowSyBl -...DanBrown980551
Do you want to learn how to model and simulate an electrical network from scratch in under an hour?
Then welcome to this PowSyBl workshop, hosted by Rte, the French Transmission System Operator (TSO)!
During the webinar, you will discover the PowSyBl ecosystem as well as handle and study an electrical network through an interactive Python notebook.
PowSyBl is an open source project hosted by LF Energy, which offers a comprehensive set of features for electrical grid modelling and simulation. Among other advanced features, PowSyBl provides:
- A fully editable and extendable library for grid component modelling;
- Visualization tools to display your network;
- Grid simulation tools, such as power flows, security analyses (with or without remedial actions) and sensitivity analyses;
The framework is mostly written in Java, with a Python binding so that Python developers can access PowSyBl functionalities as well.
What you will learn during the webinar:
- For beginners: discover PowSyBl's functionalities through a quick general presentation and the notebook, without needing any expert coding skills;
- For advanced developers: master the skills to efficiently apply PowSyBl functionalities to your real-world scenarios.
PHP Frameworks: I want to break free (IPC Berlin 2024)Ralf Eggert
In this presentation, we examine the challenges and limitations of relying too heavily on PHP frameworks in web development. We discuss the history of PHP and its frameworks to understand how this dependence has evolved. The focus will be on providing concrete tips and strategies to reduce reliance on these frameworks, based on real-world examples and practical considerations. The goal is to equip developers with the skills and knowledge to create more flexible and future-proof web applications. We'll explore the importance of maintaining autonomy in a rapidly changing tech landscape and how to make informed decisions in PHP development.
This talk is aimed at encouraging a more independent approach to using PHP frameworks, moving towards a more flexible and future-proof approach to PHP development.
Transcript: Selling digital books in 2024: Insights from industry leaders - T...BookNet Canada
The publishing industry has been selling digital audiobooks and ebooks for over a decade and has found its groove. What’s changed? What has stayed the same? Where do we go from here? Join a group of leading sales peers from across the industry for a conversation about the lessons learned since the popularization of digital books, best practices, digital book supply chain management, and more.
Link to video recording: https://bnctechforum.ca/sessions/selling-digital-books-in-2024-insights-from-industry-leaders/
Presented by BookNet Canada on May 28, 2024, with support from the Department of Canadian Heritage.
Encryption in Microsoft 365 - ExpertsLive Netherlands 2024Albert Hoitingh
In this session I delve into the encryption technology used in Microsoft 365 and Microsoft Purview. Including the concepts of Customer Key and Double Key Encryption.
The Metaverse and AI: how can decision-makers harness the Metaverse for their...Jen Stirrup
The Metaverse is popularized in science fiction, and now it is becoming closer to being a part of our daily lives through the use of social media and shopping companies. How can businesses survive in a world where Artificial Intelligence is becoming the present as well as the future of technology, and how does the Metaverse fit into business strategy when futurist ideas are developing into reality at accelerated rates? How do we do this when our data isn't up to scratch? How can we move towards success with our data so we are set up for the Metaverse when it arrives?
How can you help your company evolve, adapt, and succeed using Artificial Intelligence and the Metaverse to stay ahead of the competition? What are the potential issues, complications, and benefits that these technologies could bring to us and our organizations? In this session, Jen Stirrup will explain how to start thinking about these technologies as an organisation.
The Art of the Pitch: WordPress Relationships and SalesLaura Byrne
Clients don’t know what they don’t know. What web solutions are right for them? How does WordPress come into the picture? How do you make sure you understand scope and timeline? What do you do if sometime changes?
All these questions and more will be explored as we talk about matching clients’ needs with what your agency offers without pulling teeth or pulling your hair out. Practical tips, and strategies for successful relationship building that leads to closing the deal.
DevOps and Testing slides at DASA ConnectKari Kakkonen
My and Rik Marselis slides at 30.5.2024 DASA Connect conference. We discuss about what is testing, then what is agile testing and finally what is Testing in DevOps. Finally we had lovely workshop with the participants trying to find out different ways to think about quality and testing in different parts of the DevOps infinity loop.
Welcome to the first live UiPath Community Day Dubai! Join us for this unique occasion to meet our local and global UiPath Community and leaders. You will get a full view of the MEA region's automation landscape and the AI Powered automation technology capabilities of UiPath. Also, hosted by our local partners Marc Ellis, you will enjoy a half-day packed with industry insights and automation peers networking.
📕 Curious on our agenda? Wait no more!
10:00 Welcome note - UiPath Community in Dubai
Lovely Sinha, UiPath Community Chapter Leader, UiPath MVPx3, Hyper-automation Consultant, First Abu Dhabi Bank
10:20 A UiPath cross-region MEA overview
Ashraf El Zarka, VP and Managing Director MEA, UiPath
10:35: Customer Success Journey
Deepthi Deepak, Head of Intelligent Automation CoE, First Abu Dhabi Bank
11:15 The UiPath approach to GenAI with our three principles: improve accuracy, supercharge productivity, and automate more
Boris Krumrey, Global VP, Automation Innovation, UiPath
12:15 To discover how Marc Ellis leverages tech-driven solutions in recruitment and managed services.
Brendan Lingam, Director of Sales and Business Development, Marc Ellis
Pushing the limits of ePRTC: 100ns holdover for 100 daysAdtran
At WSTS 2024, Alon Stern explored the topic of parametric holdover and explained how recent research findings can be implemented in real-world PNT networks to achieve 100 nanoseconds of accuracy for up to 100 days.
zkStudyClub - Reef: Fast Succinct Non-Interactive Zero-Knowledge Regex ProofsAlex Pruden
This paper presents Reef, a system for generating publicly verifiable succinct non-interactive zero-knowledge proofs that a committed document matches or does not match a regular expression. We describe applications such as proving the strength of passwords, the provenance of email despite redactions, the validity of oblivious DNS queries, and the existence of mutations in DNA. Reef supports the Perl Compatible Regular Expression syntax, including wildcards, alternation, ranges, capture groups, Kleene star, negations, and lookarounds. Reef introduces a new type of automata, Skipping Alternating Finite Automata (SAFA), that skips irrelevant parts of a document when producing proofs without undermining soundness, and instantiates SAFA with a lookup argument. Our experimental evaluation confirms that Reef can generate proofs for documents with 32M characters; the proofs are small and cheap to verify (under a second).
Paper: https://eprint.iacr.org/2023/1886
GDG Cloud Southlake #33: Boule & Rebala: Effective AppSec in SDLC using Deplo...James Anderson
Effective Application Security in Software Delivery lifecycle using Deployment Firewall and DBOM
The modern software delivery process (or the CI/CD process) includes many tools, distributed teams, open-source code, and cloud platforms. Constant focus on speed to release software to market, along with the traditional slow and manual security checks has caused gaps in continuous security as an important piece in the software supply chain. Today organizations feel more susceptible to external and internal cyber threats due to the vast attack surface in their applications supply chain and the lack of end-to-end governance and risk management.
The software team must secure its software delivery process to avoid vulnerability and security breaches. This needs to be achieved with existing tool chains and without extensive rework of the delivery processes. This talk will present strategies and techniques for providing visibility into the true risk of the existing vulnerabilities, preventing the introduction of security issues in the software, resolving vulnerabilities in production environments quickly, and capturing the deployment bill of materials (DBOM).
Speakers:
Bob Boule
Robert Boule is a technology enthusiast with PASSION for technology and making things work along with a knack for helping others understand how things work. He comes with around 20 years of solution engineering experience in application security, software continuous delivery, and SaaS platforms. He is known for his dynamic presentations in CI/CD and application security integrated in software delivery lifecycle.
Gopinath Rebala
Gopinath Rebala is the CTO of OpsMx, where he has overall responsibility for the machine learning and data processing architectures for Secure Software Delivery. Gopi also has a strong connection with our customers, leading design and architecture for strategic implementations. Gopi is a frequent speaker and well-known leader in continuous delivery and integrating security into software delivery.
GDG Cloud Southlake #33: Boule & Rebala: Effective AppSec in SDLC using Deplo...
Vlite node – new sensors solution for farming
1. VLITE NODE – New sensors solution for farming<br />Zbynek Krivanek, Marek Musil, Jan Jezek, Karel Charvat<br />Czech centre for Science and Society<br />E-mail charvat@ccss.cz, <br />Abstract <br />In past years in world an extensive research and development work is being done to ensure information technology use in agriculture; long range wireless sensor network (WSN) creation for specific agricultural use. Existing WSN solutions are in experimental development phase; their implementations is not possible without the specific WSN technology developers’ assistance and they have a short working range (ability to guarantee communication between sensors only at a range of several tens of meters); therefore their implementation in large area is very expensive. Realistic WSN implementation is unthinkable without specific WSN technology that includes physical nodes, sensors, operating system, application programming environment, competence centre support. The paper describes new long distance RFID based technology implementation - VLIT NODE.<br />Keywords Wireless Sensors Network, Agriculture<br />1. Introduction<br />The importance of meteorology in agriculture has been increasing during last decades due to emerging need to access appropriate information as consequence of the increased rapid weather conditions changes. Although the quality of weather forecast has been improved constantly and, at large,<br />agriculture is benefiting from this achieved capability, in many European regions, the currently available meteorological data are not sufficient for crop production, as a lot of additional local scale data are needed to be integrated in the specific agro-meteorological models and to take the correct decision in any farm management system. To meet the farmers ambitions, especially in areas where parcels are relatively small involving the growth of “expensive” cultivars (as for the production of wine), there is the need of establishing networks of local sensors and meteorological stations. The ongoing significant advancements in sensors technologies and in_situ sensing are expected to support also the development of more systematic capabilities for assimilating all sort of in_situ measurements in agro-meteorological models, at relevant scales, to generate immediately (in real time) useful information for the farmer’s decision. At the same time, the fusion of meteorological sensors data with existing agro-production database and implementation of new online agro-meteorological models for farms could open new possibilities for farmers to increase quality of their production, to be more competitive on the market and in this way also to increase they sustainability and profit.<br />2. Objectives<br />Agro meteorological parameters have strong influence on crop growth and development, but also on the dynamics of other important biological elements, such as plant diseases and pests. The monitoring of agro-meteorological variables on the territory together with the application of simulation models, represent the basis for a correct management of cultivation methods and sanitary treatments. For the realization of such a monitoring, the development of a reference detail climatologically study of the area is required, in order to assess the climatic conditions and to identify the most representative sites where the meteorological stations for the measurements of the interested variables have to be placed. Once the strategic sites are monitored by stations, data can be collected for further processes, such as spatial interpolations and application of agro-meteorological simulation models. <br />3. Methodology<br />SENSORS <br /> A sensor is a device that measures a physical quantity and converts it into a signal which can be read by an observer or by an instrument. There exist many kinds of sensors for surveillance and intrusion detection, such as infrared, other optical, microwave-based, or other types. They, for example, video cameras, can be effectively used to support manned surveillance. There are also video-based systems that sense changes in the image and will trigger an alert. Since every sensor used for this kind of applications can be characterised by its location coordinates (changeable) and a time component, the spatial extension and near-real-time availability of sensor-originated information layers in geospatial applications create a great potential.<br />Sensors are most commonly used to make quantifiable measurements, as opposed to qualitative detection or presence sensing. For the sensor selection there are four criteria:<br />What we need to measure, this influenced type of sensors, sensors could measure almost anything, but every phenomena need different type of sensors<br />In which environment we will measure, there are different need on outdoor and indoor sensors, and also there are specific needs on sensors working in extreme conditions<br />What is required accuracy of measurement<br />The question, if the whole system is calibrated or certified<br />These four aspects could have influence on selection of sensors, but also on the cost of sensors.<br />Every sensor is described by next characteristics:<br />Transfer Function - the functional relationship between physical input signal and electrical output signal<br />Sensitivity - relationship between input physical signal and output electrical signal<br />Span or Dynamic Range - range of input physical signals that may be converted to electrical signals by the sensor<br />Accuracy or Uncertainty - largest expected error between actual and ideal output signals<br />Hysteresis - width of the expected error in terms of the measured quantity<br />Nonlinearity - maximum deviation from a linear transfer function over the specified dynamic range<br />Noise - sensors produce some output noise in addition to the output signal<br />Resolution - minimum detectable signal fluctuation<br />Bandwidth - response times to an instantaneous change in physical signal<br />When we are speaking about sensors, we usually consider both part of sensors and transducer, a sensor is a device that receives a signal or stimulus and responds with an electrical signal, while a transducer is a converter of one type of energy into another. From a signal conditioning viewpoint it is useful to classify sensors as either active or passive. An active sensor requires an external source of excitation. A passive (or self-generating) sensor generates their own electrical output signal without requiring external voltages or currents.<br /> Wireless Sensors networks (WSN)<br />The future utilization of sensors technologies will be mainly based on Wireless Sensors Network which is an emerging technology made up from tiny, wireless sensors or “motes.” Eventually, these devices will be smart enough to talk with other sensors yet small enough to fit on the head of a pin. Each mote is a tiny computer with a power supply, one or more sensors, and a communication system. One is the network independent module Smart Transducer Interface Module (STIM) that contains the transducers, its signal conditioning circuitry and a standard interface. The other is a network specific module Network Capable Application Processor (NCAP) that implements the interface to the desired control network and also implements the standard interface of the transducer module. Sensor networks are receiving a significant attention because of their many potential civilian and military applications. The design of sensor networks faces a number of challenges resulting from very demanding requirements on one side, such as high reliability of the decision taken by the network and robustness to node failure, and very limited resources on the other side, such as energy, bandwidth, and node complexity.<br />Sensor Network Systems provide a novel paradigm for managing, modelling and supporting complex systems requiring massive data gathering, with pervasive and persistent detection/monitoring capabilities. It is not therefore surprising that in recent years, a growing emphasis has been steered toward the employment of sensor networks in various technological fields: e.g. aerospace, environment monitoring, homeland security, smart buildings. A significant amount of resources has been allocated for national (USA, France, Germany) and international (e.g. European Commission) research programs targeted at developing innovative methodologies and emerging technologies in different application fields of wireless sensor network. The main features that a sensor network should have are:<br />each node should have a very low power consumption, the capability of recharging its battery or scavenging energy from the environment, and very limited processing capabilities;<br />each node should be allowed to go in stand-by mode (to save as much battery as possible) without severely degrading the connectivity of the whole network and without requiring complicated re-routing strategies; <br />the estimation/measurement capabilities of the system as a whole should significantly outperform the capabilities of each sensor and the performance should improve as the number of sensors increases, with no mandatory requirement on the transmission of the data of each single sensor toward a centralised control/processing unit; in other words, the network must be scalable and self-organising, i.e. capable of maintaining its functionality (although modifying the performance) when the number of sensor is increased1;<br />a sensor network is ultimately an event-driven system, so that what it is really necessary to guarantee is that the information about events of interest reach the appropriate control nodes, possibly through the simplest propagation mechanism, not necessarily bounded to the common OSI protocol stack layer; <br />congestion around the sink nodes should be avoided by introducing some form of distributed processing;<br />the information should flow through the network in the simplest possible way, not necessarily relying on sophisticated modulation or multiplexing techniques.<br />Summarising, the fundamental requirements of a sensor network are:<br />Very low complexity elementary sensors, associated with a low power consumption and low-cost;<br />High reliability of the decision/estimation/measurement of the network as a whole;<br />Long network life-time for low maintenance and stand-alone operation;<br />High scalability;<br />The resilience to congestion problems in traffic peak conditions.<br />In past years in world an extensive research and development work is being done to ensure information technology use in agriculture; long range wireless sensor network creation for specific agricultural use, would ensure a PA technological leap, would solve pressing problems for agriculture and would make PA widely available for farmers, even for low scale use (cranberry fields, fruit gardens, bee-gardens etc.). However for existing solutions these problems remain:<br />Existing WSN solutions are in experimental development phase; their implementation is not possible without the specific WSN technology developers’ assistance.<br />Existing WSNs have a short working range (ability to guarantee communication between sensors only at a range of several tens of meters); therefore their implementation in large area is very expensive.<br />Existing WSN technology application programming is not possible without deep WSN operating system (open source Tiny OS, commercial ZigBee etc.) knowledge, that is possible only in specialized development centers;<br />Presently known WSN physical node technologies with several hundred meters working range don’t support available Operating Systems; <br />Existing WSNs are not suited for climatic and geographical factors, as well as production manufacturing problems;<br />Realistic WSN implementation is unthinkable without specific WSN technology that includes physical nodes, sensors, operating system, application programming environment, competence centre support.<br />So it is clear, that new development is necessary. Development would include:<br />Principally new sensor nodes with communication ranges of 200-800m depending on environment, weather conditions and sensor location, that are suited for use in most of European countries; <br />Development of operating system programming that would collect data from sensor nodes and transport them via wireless network to base computer, such communication protocol configuration that would comply with respective usage target environment, as well as specific usage application programming development in to the utmost simplified environment (in language C with possibly minimal specific knowledge about operating system and WSN physical realization), that would ensure sensor control and communication between sensor nodes;<br />Development of network architecture<br />4. Winsoc Technology Description<br />WINSOC developed very innovative concept of sensor network that represents a significant departure from current proposals. Whole network is achieved by introducing a suitable coupling among adjacent, low cost, sensors, enabling a global distributed detection or estimation more accurate than that achievable by each single sensor, without the need for sending all the data to a fusion centre. The whole network is hierarchical and composed of two layers: a lower level, composed of the low cost sensors described above, responsible for gathering information from the environment and producing locally reliable decisions, and an upper level, composed of more sophisticated nodes, whose goal is to convey the information to the control centres. The key point is the interaction among the low cost sensors that increases the overall reliability, also insuring scalability and tolerance against failure and/or stand-by of some sensors, (e.g. battery recharge and energy saving). The goal was, on one side, to develop a general purpose innovative sensor network having the distributed processing capabilities described above and, on the other side, to test applications on environmental risk management where heterogeneous networks, composed of nodes having various degree of complexity and capabilities, are made to work under realistic scenarios. More specifically, the project will address applications to small landslides detection and large scale temperature field detection and monitoring. Scrutinising the state of the art of the paradigms typically employed in sensor networks, it is possible to recognise a common critical factor: the current paradigms greatly reflect (although scaled and adapted) a well known and consolidated methodological approach borrowed from TLC networks, which however has been developed to cope with totally different requirements and constraints, with respect to a sensor network. The most typical solutions try to adapt classical telecommunication protocols, except for a much greater emphasis on energy-efficient design (see, e.g., ZigBee). However, they still require rather sophisticated network protocols and management overheads in applications where the bit rate required by the sensor network is relatively small and what is really necessary is only to bring the event of interest from the source to the right control node. Typically, the congestion around the sink nodes is only alleviated, but not avoided and the network is not scalable. In WINSOC, it was envisage the development of a very innovative concept of sensor network that represents a significant departure from current proposals. The network is organized in two hierarchical levels. At the low level, there are very simple nodes that gather relevant information and interact with each other to achieve a consensus about the locally observed phenomenon. The interaction occurs through a very simple mechanism that does not require complicated modulation, MAC, or routing strategies. This interaction among the sensors is the key feature, as it improves the reliability of the local decisions and, at the same time, it yields fault tolerance and scalability. The decisions taken locally are then communicated to the upper level nodes that take care of forwarding them to the appropriate control centres.<br />5. Developments<br />Currently, there are many technologies for building wireless sensor networks. They are implemented on different platforms, but their common drawback is that they are able to guarantee the communication between sensors at a distance of only tens of meters. This is the first limited range of networks, while these networks are unaffordable. <br />Cominfo Corp. developing RFID technology with unique properties, whereby you can build a sensor networks with long-range communication, and affordable costs. Technology is internally known as VLIT. It is characterized by 868 MHz working frequency and by protocol that supports communication mode Point-To-Point, Point-To-Multipoint and the relay station of long distance over several devices. In combination with the mobile unit and the software interface being developed by The Ceske Centrum pro Vedu and Spolecnost (CCSS) presents VLIT NODE completely new and unique solution for building mobile sensor networks.<br />Technical specifications<br />The operating frequency of 868 MHz, divided into several sub bands<br />Bi-directional communication protocol of anti-collision<br />Communication distance of 200 to 800 meters depending on the environment, weather and location sensors<br />Different communication modes: challenge, selective call, communications event management <br />Support for communication Point-to-point, Point-to-multipoint, multi - hopping <br />Memory integration<br />Each tag contains a unique number (physical address) <br />The calculation of simple operations <br />Easy connectivity measuring sensors <br />Very low power consumption<br />Lifetime 6 months - 5 years (depending on battery size and type of communication)<br />Implementation of wireless sensor networks for collecting and transmission of data <br />The ability to connect to the existing mobile solutions that ensure the collection of measurement and its transmission to the Internet environment <br />Integration into the Web environment, storing data in standardized formats<br />6. Results<br />Currently were developed 200 prototypes of sensors nodes and started deployment and filed testing. Intensive filed testing is provided in Czech Republic and Latvia. It is also expected testing in Italy during this season..<br />7. Business Benefits<br />Increasing communication distance of sensors network from 50 meters to 500 meters, I will decrease number of sensors network necessary 100 times. It is important aspect for agriculture application, where first experiences demonstrate that usage sensors with communication distance between 500 meters and 1000 meters will be optimal distance for coverage farms, which such density, which allows operational usage of sensors network<br />8. Conclusions<br />The first test with new sensors started in spring 2010. Currently are new sensors prepared for real operational testing during season 2011<br />The research leading to these results received following funding:<br />LearnSense - the solution was achieved with financial support from state resources provided by the Ministry of Industry and Trade of the Czech Republic for support of project of the program “TIP-2009”<br />VLIT NODE - the solution was achieved with financial support from state resources provided by the Ministry of Industry and Trade of the Czech Republic for support of project of the program “TIP-2009” with registration number FR—TI1/523.<br />enviroGRIDS @ Black Sea Catchment -the solution was achieved with financial co-funding by the European Commission within the Seventh Framework Programme with registration number 226740 and name “Building Capacity for a Black Sea Catchment Observation and Assessment System supporting Sustainable Development”<br />References<br />[1] Capodieci et al. 2009, Wireless Sensor Networks with Self-Organisation Capabilities for Critical and Emergency Applications (Publishable Final Activity Report), www.winsoc.org<br />[2] Charvat et al. 2008, Spatial Data Infrastructure and Geovisualisation in Emergency Management, H. Pasman and I.A. Kirillov (eds.), Resilience of Cities to Terrorist and other Threats, Springer Science + Business Media B.V. 2008<br />[3] Charvat et al., 2009, INSPIRE, GMES and GEOSS Activities, Methods and Tools towards a Single Information Space in Europe for the Environment<br />Riga, Latvia<br />[4] Charvat et al. 2010, enviroGRIDS sensor data use and integration guideline<br />www.envirogrids.net<br />[5] Gnip et al. 2008, In situ sensors and Prefarm system(p.255-262), conference proceeding book, IAALD AFITA WCCA2008, Tokyo , Japan.<br />[6] Wilson, 2005, Sensor Technology Handbook, Elsevier Inc, UK<br />