The document discusses social innovation led by Hitachi, focusing on several case studies of technologies and services developed through co-creation with customers and partners to solve social issues. These include a care information platform to support healthy aging in communities, autonomous driving systems, smart cities and mobility services, platforms for local production and consumption, and digital technologies for farming. The case studies illustrate Hitachi's approach of integrating technology with customer needs and local knowledge to drive positive social change.
The document repeatedly states that the copyright of the content belongs to Ikki Inoue in 2017 and that all rights are reserved. It lists the copyright notice over 30 times.
This document summarizes the challenges of climate change in the context of other issues facing agriculture and food security. It shows that climate change will slow progress towards ending hunger by 2030, though socioeconomic factors will dominate in the medium term. The impacts of climate change on food prices and hunger are projected to increase over time. Increased investment in agricultural research and development as well as irrigation expansion and water management can help offset climate change impacts through 2050 by improving agricultural supply, reducing hunger and water use, and increasing GDP, according to models. Specific solutions will depend on location-specific contexts and choices made by individuals, businesses and governments.
#Hadoop #meetup @hug_uk event at @facebook in #London on 26 April 2017
https://www.meetup.com/hadoop-users-group-uk/events/238368183/
https://hadoopmeetupinlondon.splashthat.com/
Great Place to Work PowerPoint Presentation DesignerSlides IQ
The document discusses how disruption is now the new normal and sustained, gradual innovation can lead to disruption. It provides examples of innovative projects from Great Place to Work like a solar cooler and a women's entrepreneur bar. The document argues disruption can apply not just to products and services but also communication methods. It outlines Great Place to Work's approach of engaging communities through multiple touchpoints and focusing on empowering people.
n the age of IoT, sensors and network technology are being developed at a rapid pace, and through the use of wearable devices and robots, it is possible to obtain a huge volume of sensory data in a short period of time. AI has become essential for processing such volumes of data.
In the past, AI was developed for specific uses, meaning each application required specialized settings, development and optimization. Kazuo Yano led a project to develop artificial intelligence that can be used for multiple purposes: Hitachi AI Technology/H. This AI creates programs from data based on the objective set for each project, enabling it to find the optimal solution for any situation.
Yano also developed a sensor that obtains human behavioral data, and discovered that it could be used to measure people’s level of happiness. Based on the quantified happiness data, he proposed to employees behaviors at the workplace that could improve productivity, such as communication habits and time management. As such, Yano opened the door to new uses of big data for implementing improvements in the workplace. The Head Prize is awarded for his pioneering achievements in the field of AI and in expectation of further developments.
Health Checking: A not-so-trivial task in the distributed containerized worldAll Things Open
The document discusses the challenges of implementing health checking in distributed and containerized systems. It covers how different technologies like Kubernetes, Mesos, Docker and AWS approach health checking. It also discusses strategies for scaling health checks in large clusters and challenges like avoiding downtime when tasks need to be restarted. The document seems to be notes from a talk or presentation on health checking in modern distributed systems.
The document discusses whether Malaysia is ready for an Internet of Things (IoT) boom. It outlines how Malaysia's young, connected population and rapid urbanization are driving IoT adoption. The government is also actively supporting IoT through initiatives like the National IoT Strategic Roadmap. This aims to make Malaysia a regional IoT hub by 2020 and improve areas like smart cities and transportation. The document concludes that with its pro-technology environment, growing digital economy, and government backing, Malaysia is well positioned for an IoT boom.
The document repeatedly states that the copyright of the content belongs to Ikki Inoue in 2017 and that all rights are reserved. It lists the copyright notice over 30 times.
This document summarizes the challenges of climate change in the context of other issues facing agriculture and food security. It shows that climate change will slow progress towards ending hunger by 2030, though socioeconomic factors will dominate in the medium term. The impacts of climate change on food prices and hunger are projected to increase over time. Increased investment in agricultural research and development as well as irrigation expansion and water management can help offset climate change impacts through 2050 by improving agricultural supply, reducing hunger and water use, and increasing GDP, according to models. Specific solutions will depend on location-specific contexts and choices made by individuals, businesses and governments.
#Hadoop #meetup @hug_uk event at @facebook in #London on 26 April 2017
https://www.meetup.com/hadoop-users-group-uk/events/238368183/
https://hadoopmeetupinlondon.splashthat.com/
Great Place to Work PowerPoint Presentation DesignerSlides IQ
The document discusses how disruption is now the new normal and sustained, gradual innovation can lead to disruption. It provides examples of innovative projects from Great Place to Work like a solar cooler and a women's entrepreneur bar. The document argues disruption can apply not just to products and services but also communication methods. It outlines Great Place to Work's approach of engaging communities through multiple touchpoints and focusing on empowering people.
n the age of IoT, sensors and network technology are being developed at a rapid pace, and through the use of wearable devices and robots, it is possible to obtain a huge volume of sensory data in a short period of time. AI has become essential for processing such volumes of data.
In the past, AI was developed for specific uses, meaning each application required specialized settings, development and optimization. Kazuo Yano led a project to develop artificial intelligence that can be used for multiple purposes: Hitachi AI Technology/H. This AI creates programs from data based on the objective set for each project, enabling it to find the optimal solution for any situation.
Yano also developed a sensor that obtains human behavioral data, and discovered that it could be used to measure people’s level of happiness. Based on the quantified happiness data, he proposed to employees behaviors at the workplace that could improve productivity, such as communication habits and time management. As such, Yano opened the door to new uses of big data for implementing improvements in the workplace. The Head Prize is awarded for his pioneering achievements in the field of AI and in expectation of further developments.
Health Checking: A not-so-trivial task in the distributed containerized worldAll Things Open
The document discusses the challenges of implementing health checking in distributed and containerized systems. It covers how different technologies like Kubernetes, Mesos, Docker and AWS approach health checking. It also discusses strategies for scaling health checks in large clusters and challenges like avoiding downtime when tasks need to be restarted. The document seems to be notes from a talk or presentation on health checking in modern distributed systems.
The document discusses whether Malaysia is ready for an Internet of Things (IoT) boom. It outlines how Malaysia's young, connected population and rapid urbanization are driving IoT adoption. The government is also actively supporting IoT through initiatives like the National IoT Strategic Roadmap. This aims to make Malaysia a regional IoT hub by 2020 and improve areas like smart cities and transportation. The document concludes that with its pro-technology environment, growing digital economy, and government backing, Malaysia is well positioned for an IoT boom.
This document discusses distributed tracing in Go applications. It explains what distributed tracing is and why it is useful for tracking requests across multiple services. It then provides an overview of common tracing tools and standards like OpenTracing and Jaeger that can be used to implement distributed tracing. Finally, it demonstrates distributed tracing in action with a demo of OpenTracing and Jaeger.
The document discusses service design and culture. It notes that culture is more important than strategy, and that small, playful changes can have a big impact on culture. It advocates adopting an approach focused on building tribe, and emphasizes the importance of measurement to assess cultural changes.
Connected Things 2017 explores how to accelerate the adoption of the Internet of Things and
how IoT could have the biggest impact on people, places and things.
Harel Kodesh, Vice President, Predix & CTO, GE Digital
Mac Devine, VP & CTO, Emerging Technology & Advanced Innovation, IBM Cloud Division
Alan Southall, SVP of Engineering, Head of IoT Predictive Maintenance, SAP
David Friend, CEO, BlueArchive
テスト自動化 はじめの一歩 (Test Automation -First Step-) in アジャイルひよこクラブ #agile_hiyokoteyamagu
The document contains multiple repetitions of the copyright notice for Yahoo Japan Corporation from 2017, asserting their full rights are reserved. It provides attribution but no other substantive information beyond establishing the copyright holder and year.
The document discusses JapanTaxi's taxi dispatching system. It describes the system's architecture including its use of Android and Java for the taxi control unit and Android Bluetooth for communicating with an IRIS Bluetooth module. The system manages taxi dispatching and payments and collects trip and vehicle diagnostic data for analysis.
The document discusses principles of writing clean code, including keeping code simple with fewer lines, using descriptive names, adding comments to explain complex code, and regularly refactoring code for readability and maintainability. It encourages developers to periodically review their code to identify areas for improvement and clean up. The document appears to be from a presentation on clean code best practices.
When IGA meets PAM ... through their mutual friend SCIMKelly Grizzle
IGA and PAM are two technologies that historically have been siloed, with IGA focused on identity governance and administration and PAM focused on controlling access to privileged accounts. SCIM (System for Cross-Domain Identity Management) provides a standardized API and data model to integrate IGA and PAM by allowing user and group information to be shared between the systems. The SCIM PAM extension further augments SCIM to define concepts for managing privileged data and access control between IGA and PAM, joining these two important security domains.
Velocity and Volatility: Culture and Strategy in the Digital AgeEthan Pack
The document discusses how digital transformation requires changes to organizational culture and strategy. It emphasizes that culture can help or hinder strategy, noting that culture "eats strategy". It identifies four key aspects of culture that are important for digital transformation - communication and collaboration, establishing a common vision, change management abilities, and a committed workforce. It argues that a digital business platform can help support the necessary cultural and strategic changes by enabling things like business-outcome oriented architecture and a digital workplace.
The document is a report from Alex G. Lee of Xanadu Big Data about the ODSC Data Science Conference and AI Expo that took place on May 6, 2017. However, the document does not contain any actual summarizable content, as it is composed entirely of copyright notices and does not discuss any events, presentations, or key findings from the conference.
Machine Learning, Artificial Intelligence (AI), and the Future of Big Data Analytics
Making Big Data Fit – Discovering where the platform will work for you
Modernizing BI & Analytics
Data Science in the Enterprise
Big Data Bootcamp is targeted towards both technical and non-technical people who want to understand the emerging world of Big Data, with a specific focus on Hadoop, Spark, NoSQL, Data Science, Machine Learning, Artificial Intelligence & Deep Learning.
View of Scalable Machine Learning in R and Python with H2O Seminar
Boston AI & Deep learning Meetup
The focus of this presentation is scalable machine learning using the h2o R and Python packages. H2O is an open source, distributed machine learning platform designed for big data, with the added benefit that it's easy to use on a laptop (in addition to a multi-node Hadoop or Spark cluster). The core machine learning algorithms of H2O are implemented in high-performance Java, however, fully-featured APIs are available in R, Python, Scala, REST/JSON, and also through a web interface.
Since H2O's algorithm implementations are distributed, this allows the software to scale to very large datasets that may not fit into RAM on a single machine. H2O currently features distributed implementations of Generalized Linear Models, Gradient Boosting Machines, Random Forest, Deep Neural Nets, Stacked Ensembles (aka "Super Learners"), dimensionality reduction methods (PCA, GLRM), clustering algorithms (K-means), anomaly detection methods, among others.
R and Python code with H2O machine learning code examples will be demoed live and will be made available on GitHub for participants to follow along on their laptops if they choose. For those interested in running the code on a multi-node Amazon EC2 cluster, an H2O AMI is also available.
Optimizing Gradle Builds - Gradle DPE Tour Berlin 2024Sinan KOZAK
Sinan from the Delivery Hero mobile infrastructure engineering team shares a deep dive into performance acceleration with Gradle build cache optimizations. Sinan shares their journey into solving complex build-cache problems that affect Gradle builds. By understanding the challenges and solutions found in our journey, we aim to demonstrate the possibilities for faster builds. The case study reveals how overlapping outputs and cache misconfigurations led to significant increases in build times, especially as the project scaled up with numerous modules using Paparazzi tests. The journey from diagnosing to defeating cache issues offers invaluable lessons on maintaining cache integrity without sacrificing functionality.
AI for Legal Research with applications, toolsmahaffeycheryld
AI applications in legal research include rapid document analysis, case law review, and statute interpretation. AI-powered tools can sift through vast legal databases to find relevant precedents and citations, enhancing research accuracy and speed. They assist in legal writing by drafting and proofreading documents. Predictive analytics help foresee case outcomes based on historical data, aiding in strategic decision-making. AI also automates routine tasks like contract review and due diligence, freeing up lawyers to focus on complex legal issues. These applications make legal research more efficient, cost-effective, and accessible.
Design and optimization of ion propulsion dronebjmsejournal
Electric propulsion technology is widely used in many kinds of vehicles in recent years, and aircrafts are no exception. Technically, UAVs are electrically propelled but tend to produce a significant amount of noise and vibrations. Ion propulsion technology for drones is a potential solution to this problem. Ion propulsion technology is proven to be feasible in the earth’s atmosphere. The study presented in this article shows the design of EHD thrusters and power supply for ion propulsion drones along with performance optimization of high-voltage power supply for endurance in earth’s atmosphere.
Generative AI Use cases applications solutions and implementation.pdfmahaffeycheryld
Generative AI solutions encompass a range of capabilities from content creation to complex problem-solving across industries. Implementing generative AI involves identifying specific business needs, developing tailored AI models using techniques like GANs and VAEs, and integrating these models into existing workflows. Data quality and continuous model refinement are crucial for effective implementation. Businesses must also consider ethical implications and ensure transparency in AI decision-making. Generative AI's implementation aims to enhance efficiency, creativity, and innovation by leveraging autonomous generation and sophisticated learning algorithms to meet diverse business challenges.
https://www.leewayhertz.com/generative-ai-use-cases-and-applications/
This document discusses distributed tracing in Go applications. It explains what distributed tracing is and why it is useful for tracking requests across multiple services. It then provides an overview of common tracing tools and standards like OpenTracing and Jaeger that can be used to implement distributed tracing. Finally, it demonstrates distributed tracing in action with a demo of OpenTracing and Jaeger.
The document discusses service design and culture. It notes that culture is more important than strategy, and that small, playful changes can have a big impact on culture. It advocates adopting an approach focused on building tribe, and emphasizes the importance of measurement to assess cultural changes.
Connected Things 2017 explores how to accelerate the adoption of the Internet of Things and
how IoT could have the biggest impact on people, places and things.
Harel Kodesh, Vice President, Predix & CTO, GE Digital
Mac Devine, VP & CTO, Emerging Technology & Advanced Innovation, IBM Cloud Division
Alan Southall, SVP of Engineering, Head of IoT Predictive Maintenance, SAP
David Friend, CEO, BlueArchive
テスト自動化 はじめの一歩 (Test Automation -First Step-) in アジャイルひよこクラブ #agile_hiyokoteyamagu
The document contains multiple repetitions of the copyright notice for Yahoo Japan Corporation from 2017, asserting their full rights are reserved. It provides attribution but no other substantive information beyond establishing the copyright holder and year.
The document discusses JapanTaxi's taxi dispatching system. It describes the system's architecture including its use of Android and Java for the taxi control unit and Android Bluetooth for communicating with an IRIS Bluetooth module. The system manages taxi dispatching and payments and collects trip and vehicle diagnostic data for analysis.
The document discusses principles of writing clean code, including keeping code simple with fewer lines, using descriptive names, adding comments to explain complex code, and regularly refactoring code for readability and maintainability. It encourages developers to periodically review their code to identify areas for improvement and clean up. The document appears to be from a presentation on clean code best practices.
When IGA meets PAM ... through their mutual friend SCIMKelly Grizzle
IGA and PAM are two technologies that historically have been siloed, with IGA focused on identity governance and administration and PAM focused on controlling access to privileged accounts. SCIM (System for Cross-Domain Identity Management) provides a standardized API and data model to integrate IGA and PAM by allowing user and group information to be shared between the systems. The SCIM PAM extension further augments SCIM to define concepts for managing privileged data and access control between IGA and PAM, joining these two important security domains.
Velocity and Volatility: Culture and Strategy in the Digital AgeEthan Pack
The document discusses how digital transformation requires changes to organizational culture and strategy. It emphasizes that culture can help or hinder strategy, noting that culture "eats strategy". It identifies four key aspects of culture that are important for digital transformation - communication and collaboration, establishing a common vision, change management abilities, and a committed workforce. It argues that a digital business platform can help support the necessary cultural and strategic changes by enabling things like business-outcome oriented architecture and a digital workplace.
The document is a report from Alex G. Lee of Xanadu Big Data about the ODSC Data Science Conference and AI Expo that took place on May 6, 2017. However, the document does not contain any actual summarizable content, as it is composed entirely of copyright notices and does not discuss any events, presentations, or key findings from the conference.
Machine Learning, Artificial Intelligence (AI), and the Future of Big Data Analytics
Making Big Data Fit – Discovering where the platform will work for you
Modernizing BI & Analytics
Data Science in the Enterprise
Big Data Bootcamp is targeted towards both technical and non-technical people who want to understand the emerging world of Big Data, with a specific focus on Hadoop, Spark, NoSQL, Data Science, Machine Learning, Artificial Intelligence & Deep Learning.
View of Scalable Machine Learning in R and Python with H2O Seminar
Boston AI & Deep learning Meetup
The focus of this presentation is scalable machine learning using the h2o R and Python packages. H2O is an open source, distributed machine learning platform designed for big data, with the added benefit that it's easy to use on a laptop (in addition to a multi-node Hadoop or Spark cluster). The core machine learning algorithms of H2O are implemented in high-performance Java, however, fully-featured APIs are available in R, Python, Scala, REST/JSON, and also through a web interface.
Since H2O's algorithm implementations are distributed, this allows the software to scale to very large datasets that may not fit into RAM on a single machine. H2O currently features distributed implementations of Generalized Linear Models, Gradient Boosting Machines, Random Forest, Deep Neural Nets, Stacked Ensembles (aka "Super Learners"), dimensionality reduction methods (PCA, GLRM), clustering algorithms (K-means), anomaly detection methods, among others.
R and Python code with H2O machine learning code examples will be demoed live and will be made available on GitHub for participants to follow along on their laptops if they choose. For those interested in running the code on a multi-node Amazon EC2 cluster, an H2O AMI is also available.
Optimizing Gradle Builds - Gradle DPE Tour Berlin 2024Sinan KOZAK
Sinan from the Delivery Hero mobile infrastructure engineering team shares a deep dive into performance acceleration with Gradle build cache optimizations. Sinan shares their journey into solving complex build-cache problems that affect Gradle builds. By understanding the challenges and solutions found in our journey, we aim to demonstrate the possibilities for faster builds. The case study reveals how overlapping outputs and cache misconfigurations led to significant increases in build times, especially as the project scaled up with numerous modules using Paparazzi tests. The journey from diagnosing to defeating cache issues offers invaluable lessons on maintaining cache integrity without sacrificing functionality.
AI for Legal Research with applications, toolsmahaffeycheryld
AI applications in legal research include rapid document analysis, case law review, and statute interpretation. AI-powered tools can sift through vast legal databases to find relevant precedents and citations, enhancing research accuracy and speed. They assist in legal writing by drafting and proofreading documents. Predictive analytics help foresee case outcomes based on historical data, aiding in strategic decision-making. AI also automates routine tasks like contract review and due diligence, freeing up lawyers to focus on complex legal issues. These applications make legal research more efficient, cost-effective, and accessible.
Design and optimization of ion propulsion dronebjmsejournal
Electric propulsion technology is widely used in many kinds of vehicles in recent years, and aircrafts are no exception. Technically, UAVs are electrically propelled but tend to produce a significant amount of noise and vibrations. Ion propulsion technology for drones is a potential solution to this problem. Ion propulsion technology is proven to be feasible in the earth’s atmosphere. The study presented in this article shows the design of EHD thrusters and power supply for ion propulsion drones along with performance optimization of high-voltage power supply for endurance in earth’s atmosphere.
Generative AI Use cases applications solutions and implementation.pdfmahaffeycheryld
Generative AI solutions encompass a range of capabilities from content creation to complex problem-solving across industries. Implementing generative AI involves identifying specific business needs, developing tailored AI models using techniques like GANs and VAEs, and integrating these models into existing workflows. Data quality and continuous model refinement are crucial for effective implementation. Businesses must also consider ethical implications and ensure transparency in AI decision-making. Generative AI's implementation aims to enhance efficiency, creativity, and innovation by leveraging autonomous generation and sophisticated learning algorithms to meet diverse business challenges.
https://www.leewayhertz.com/generative-ai-use-cases-and-applications/
Prediction of Electrical Energy Efficiency Using Information on Consumer's Ac...PriyankaKilaniya
Energy efficiency has been important since the latter part of the last century. The main object of this survey is to determine the energy efficiency knowledge among consumers. Two separate districts in Bangladesh are selected to conduct the survey on households and showrooms about the energy and seller also. The survey uses the data to find some regression equations from which it is easy to predict energy efficiency knowledge. The data is analyzed and calculated based on five important criteria. The initial target was to find some factors that help predict a person's energy efficiency knowledge. From the survey, it is found that the energy efficiency awareness among the people of our country is very low. Relationships between household energy use behaviors are estimated using a unique dataset of about 40 households and 20 showrooms in Bangladesh's Chapainawabganj and Bagerhat districts. Knowledge of energy consumption and energy efficiency technology options is found to be associated with household use of energy conservation practices. Household characteristics also influence household energy use behavior. Younger household cohorts are more likely to adopt energy-efficient technologies and energy conservation practices and place primary importance on energy saving for environmental reasons. Education also influences attitudes toward energy conservation in Bangladesh. Low-education households indicate they primarily save electricity for the environment while high-education households indicate they are motivated by environmental concerns.
Digital Twins Computer Networking Paper Presentation.pptxaryanpankaj78
A Digital Twin in computer networking is a virtual representation of a physical network, used to simulate, analyze, and optimize network performance and reliability. It leverages real-time data to enhance network management, predict issues, and improve decision-making processes.
DEEP LEARNING FOR SMART GRID INTRUSION DETECTION: A HYBRID CNN-LSTM-BASED MODELijaia
As digital technology becomes more deeply embedded in power systems, protecting the communication
networks of Smart Grids (SG) has emerged as a critical concern. Distributed Network Protocol 3 (DNP3)
represents a multi-tiered application layer protocol extensively utilized in Supervisory Control and Data
Acquisition (SCADA)-based smart grids to facilitate real-time data gathering and control functionalities.
Robust Intrusion Detection Systems (IDS) are necessary for early threat detection and mitigation because
of the interconnection of these networks, which makes them vulnerable to a variety of cyberattacks. To
solve this issue, this paper develops a hybrid Deep Learning (DL) model specifically designed for intrusion
detection in smart grids. The proposed approach is a combination of the Convolutional Neural Network
(CNN) and the Long-Short-Term Memory algorithms (LSTM). We employed a recent intrusion detection
dataset (DNP3), which focuses on unauthorized commands and Denial of Service (DoS) cyberattacks, to
train and test our model. The results of our experiments show that our CNN-LSTM method is much better
at finding smart grid intrusions than other deep learning algorithms used for classification. In addition,
our proposed approach improves accuracy, precision, recall, and F1 score, achieving a high detection
accuracy rate of 99.50%.
Redefining brain tumor segmentation: a cutting-edge convolutional neural netw...IJECEIAES
Medical image analysis has witnessed significant advancements with deep learning techniques. In the domain of brain tumor segmentation, the ability to
precisely delineate tumor boundaries from magnetic resonance imaging (MRI)
scans holds profound implications for diagnosis. This study presents an ensemble convolutional neural network (CNN) with transfer learning, integrating
the state-of-the-art Deeplabv3+ architecture with the ResNet18 backbone. The
model is rigorously trained and evaluated, exhibiting remarkable performance
metrics, including an impressive global accuracy of 99.286%, a high-class accuracy of 82.191%, a mean intersection over union (IoU) of 79.900%, a weighted
IoU of 98.620%, and a Boundary F1 (BF) score of 83.303%. Notably, a detailed comparative analysis with existing methods showcases the superiority of
our proposed model. These findings underscore the model’s competence in precise brain tumor localization, underscoring its potential to revolutionize medical
image analysis and enhance healthcare outcomes. This research paves the way
for future exploration and optimization of advanced CNN models in medical
imaging, emphasizing addressing false positives and resource efficiency.
VARIABLE FREQUENCY DRIVE. VFDs are widely used in industrial applications for...PIMR BHOPAL
Variable frequency drive .A Variable Frequency Drive (VFD) is an electronic device used to control the speed and torque of an electric motor by varying the frequency and voltage of its power supply. VFDs are widely used in industrial applications for motor control, providing significant energy savings and precise motor operation.
그럼 이러게 변화 한 가치의 예를 소개 합니다.
덴마크 코펜하게 열차의 예를 소개합니다.
역에 센서를 통해 승객수를 파악하여, 승객수에따라 열차가 도착하여 정차 하는 시간을 최적화 하여 다이어로 자동 제어합니다.
과거의 KPI는 정시 도착/정시 출발이 가치였습니다만,
그러나, 승객의 수에 따라 열차 정차 시간 조정 하여 전체 승객수의 토탈 정체 시간을 줄여 주는
그러므로 괘적함을 실현하며, 더불어 열차의 운행 수도 최적화 하여 성에너지에도 공현
히다찌의 철도기술인 OT와 데이터 수집/분석하는 IT의 기술을 합쳐서 사회 인프라의 혁신에 도전하는 좋은 사례라고 생각
우리은 디지털 기술을 활용하여 사회이노베이션사업을 주력 4분야로 가속화 합니다.봄
예를 들어 산업 분야에서는 제조 설비에 가동상황이나, 코스트의 가시화부터 시작하여
작업의 효율화 코스트 삭감, 매출 향상, 업적확대까지 발전 시켜 나갈것.
그래서 공장의 리드타임을 줄이는 것 뿐만 아니라, 물류/금융 결재까지 일괄적 개선으로 밸류체인 전체를 연결해 감
이러한 혁신적인 서비스 창출과 큰 과제 해결을 위해 가치를 연속적으로 이어 나가도록 생각함.
다음 제 3장에서는 이노베이션을 실현하는 Co-Creation 시스템에 대하여 소개함.
Co-Creation이야말로 이노베이션의 원천이라고 생각합니다.
여러분과 같이 아이디어를 모아서 디지털화를 가속해 나가고 싶다.
이 이노베이션 포럼이 여러분과 같이 Co-Creation을 시작하는 장이 되었으면 합니다.
Co-Creation을 위해서는 안심/안전한 플랫폼이 필요
히다찌 2016 5부터 Co-Creation에 의한 가치 창출을 위한 기반으로 Lumada 제공을 개시
루마다는 그냥 OS/소프트웨어가 아니다
AI/빅데이이터 해석과 같은 기술적인 요소, 독자의 Co-Creation 프레임워크인 넥스피어리어스를 양축으로 하여
가치를 창출하기 위한 기반입니다.
히다찌는 약 1년 반동안 루마다는 진화
먼저 Co-Creation의 프레임워크인 넥스피리언스부터 설명
사회 이노베이션에는 무엇이 필요할까요?
공감 가능한 비젼이나 목표와 많은 사람의 아이디어가 필요
이것을 실현하기 위한 수단이 필요
종래 예측이 곤란
가치가 ‘물건에서 어떠한 것’때에는
큰 비전을 공감하는 것이 중요합니다.
이러한 공감이 새로운 힘이 됩니다.
히다찌 넥스피리언스는 이노베이션을 위한 공감 형성을 위해
중요하게 생각하는 것이 2가지.
먼저 첫째가 인간을 위한 미래를 그리는 것.
급격한 변화가 일어나고 있는 디지털 사회에서는
사람들의 미래가 어떻게 될지, 어떻게 해야 할 지를 상정하고
Co-Creation해 나가는 것이 중요합니다.
히다찌는 미래의 전조를 포착하여 미래를 그리는 비전 디자인을 통하여
다양한 툴을 준비해두었습니다.
화면에서 보시는 것처럼 미래를 같이 생각 하는 기회로 삼고자 히다찌가 예로서 그린 것들을
히다찌 홈페이지와 동영상을 올리고 있음.
고령자의 편안한 지원이라는 시선 뿐아니라 디지털 기술이 사람에게 어떻게 다가 올 수 있는지
다양한 시선으로 영상화 하고 있음
꼭 봐
두번째가
사람들의 행복과 감동을 가져다 주는 것
사람들이 어떨 때 기뻐하고 감동하는지 파악하면서
제품 서비스/개발을 하는 EX-Approch 수법을 전개 함
EX어프로치는 기존의 SI 서비스의 초상류 공정이나 신사업 서비스에
고객과 히다찌가 Co-Creation하기 위한 수법입니다.
구체적으로는 고객과 같이 컨설턴트/디자이너/SE와 같이 타분야의 전문가와 팀을 만듬
그리고 사람들이 제품과 서비스를 사용하면서 무엇을 좋아하고 감동에 이르는지 관찰하면서
이용자가 중요하게 생각 하는 서비스를 검토합니다.
최근 사례로서 미츠이 부동산의 오피스빌딩에서 신서비스를 제공하기 위한 것이 잇습니다.
이번의 ‘지금 이후의 오피스’라는테마로 워크샵을 실시
Co-Creation의 가치를 설명하는 것이 꽤한 어려운 부분이 있어 실제 Co-Creation의 현장을 영상을 통해 소개 합니다.
EX어프로치는 말로는 설명하기 힘듭니다.
실제 이 사례는 치바현의 스마트시티의 개발시에 EX어프로치의 효과를 실감한 프로젝트리더가
간사이로 전근을 가서, 칸사이 버전으로 재 기획한 것입니다 덕분에 파트너로써의 깊은 신뢰가 형성되었다.
Co-Creation으로 제안된 아이디어들은 실증검증을 통하여 실전에 실현하는 것을 목표로 하고 있습니다.
다음으로는 루마다의 기술기반인 IoT 플랫폼의 진화를 간단히 설명하겠습니다.
이번 9월에 IoT플랫폼 아키텍쳐를 크게 바꿔
2.0으로 제창 글로발 공급함
특징 하나는 히다찌 독자 디지털트윈인 어셋 아바타가 있음
기업이나 공장의 어셋을 디지털상에 재현함
센싱데이터를 기반으로 어셋 상태를 가시화하여 관리의 효율을 올리고 어셋의 최적화를 실현
또한 Open 플랫폼으로 다양한 파트너의 센싱 정보를 연계 하는 것이 가능
고객 가치 최대화를 위한 큰 에코시스템으로서 개선해 나가고자 합니다
루마다는 지원하는 코어 기술로는 작년 소개한 AI와 로보틱스가 잇늠
AI는
다목적 AI H, 대화형 AI, 화상 해석 AI등 다양한 AI나 제품 서비로 제공하고 있습니다.
AI의 활용에 중요한 것은
사람과 공종하며 사람을 지원하는 AI라는 것.
히다찌는 효율화를 위한 비즈니스 가치 뿐아니라
사람의 삶을 더욱 윤택하게 하는 AI의 개발이나 실증을 진행 하고 있음.
올 3월에 AI를 활용한 화상해석으로 사람의 100개 이상 특징을 실시간 특정
발견,개발
종래는 복수의 카메라로 공항 역 쇼핑 보안을 실시 하던 곳을 활용하여
미아찾기나 배회자 특정 인물 발견이 가능
이와 같은 히다찌는 AI를 통해
사람이 안심 안전한 사회에 공헌 목표
로보틱스는 작년 소개 휴머노이드 에뮤 개발 계속
JR동경역, 하네다 공항, 다이버시티에 고객, 관광객에게 길안내 등 실증 중
이것이 다이버시티 영상.
스스로 질문 성장하는 대화형 AI도 도입.
이후 인간의 삶이 좀더 쾌적할 수 있도록 AI나 로봇 실용화 할 생각
루마다를 활용하여 고객과의 Co-Creation을 해 나가고자 함.
루마타 Co-Creation 특징
과제공유/가시화 운영 보수까지 EtoE 로 같이 가치 창출
히다찌는 사회이노베이션 파트너로써 밸류체인의 상류에서 하류까지 일관/괄적으로 고객 지원 해 옴
고객과 Co-Creation하여 가치 창출한 예를 소개
루마다 활용. 차세대 모노쯔꾸리 실현을 도전
오쿠마.히다찌는 오쿠마의 공작기기제조 차세대 모노쯔꾸리 도전
‘단 납기 수주’, ‘급격한 납기/사양 변경’에 의한 생산 계획이 바뀌는
‘초다품종/소량생산’의 생산 현장입니다.
IoT 활용, 생산계획의 가시화, 생산진척 데이터, 설비 가동 데이터 활용, IC태크 활용으로 부품 최적 공급
가동 상황 감시 시스템 연계 하여 버틀렉을 검지하는 매스커스터머제이션
차세대 모노쯔쿠리 실증을 시작 함
오쿠마 담당자로부터 히다찌와 Co-Creation에 관한 의견을 기대하는 바를 들었음. 보자.
해외에서도 Co-Creation을 넓힘.
미국 로지스틱스와 복수의 Co-Creation을 실현.
그들의 쌓여진 데이터를 히다찌 빅데이터 해석기술을 적용
부가가치 창출.
20만대가 넘는 차량의 가동율과 안전성 향상으로 고객의 경영 지표 개선에 공헌
한편 디지털화 IoT진화의 폐혜로는 사이버 보안 리스크가 잇음
5월에 랜샘웨어가 히다찌에도 영향
본 피혜를 교훈으로 거번넌스 재 작성 및 전개
그러나, 사이버 공격 타켓이 생산 현장에서 발전소나 철도등 사회 인프라까지 이름.
이러한 공격시, 현장에서 적절히 행동하고 정보를 보아 경시청에서 판단.
이런 일련의 동작이 바로 실행 될 수 있도록 지금부터 훈련이 중요
여기서 OT/IT 둘 다 있는 히다찌 강점으로 세계 보안 선진국 이스라엘 사이버짐과 Co-Creation
오미카 사무소와/전력/철도등과 사이버 방지 서비스 개시.
북미에서 만들어진 전력소비 최소화 하는 에너지 관리 솔루션을 루마다에 실음
이를 세계 각지에서 이용 가능한 유즈케이스에 올림
지역의 고객에 맞는 최소코스트로 적용이 가능
루마다활용의 솔루션 쇼케이스화 하여 N배화 하는 것이 가능
고객와 의논 여러 아이디어를 같이 공감하는 공간을 세계에 설치
연간 200건 PoC 104건으로 증가
이노베이션 리드하는 인간/네트워크 만들기에도 집중
이노베이션 창조는 역시 인간
사원 한명의 창의적 활동이 기업과 사회를 리드
이노베이티브한 인재증가는 어떻게 하면 좋을까?
비즈니스를 리드하는 인재를 늘릴려면 어떻게 하면 좋을 까?
실제 큰 성과를 이룬 인재의 데이터를 분석,
변혁에 필요한 인재의 요건
하이퍼포먼의 사원의 특징을 명확히 함.
데이터 분석과 인사담당자의 평가를 반복하여
필요한 인재상을 명확히 함
2017년 입사 채용 시 이 인재상을 적용하여 입사사원의 특징이 월하는 방향으로 흐름
이렇게 히다찌가 물건 파는 회사에서 디지털 솔루션을 제공하는 기업으로 전환을 위한 큰 변혁기를 겪고 있음
이미 많은 활약을 하고 있는 사원들도 큰 변혁 필요.
좋은 제품/시스템을 파는 발상뿐 아니라 고객과 함께 과제를 발견하고 솔루션을 찾아 내는 사회 이노베이션 커어 인재도 육성
신입부터 기존 활약 사원까지 다양한 레벨에서 이노베이션을 하고 활력있는 인재를 만들어 나감
이런 인재가 생기있게 일 할수 있는 것이 보다 나은 아이디어와 창의가 가능
2016 12부터 보다 다양한 사람이 보다 생기 있게 일 할 수 있는 환경 구축 만들기
Work Life Innovation 운동을 하고 잇음
단순히 잔업시간 줄이는 것 말고 최대 효과를 이루기 위해서는
한사람 한사람이 보내는 시간이 이래서 될까라는 나 부터 사원에게 물어
사원의 이야기들어 큰 골격을 만들어 가는 개혁을하고 있음.
예를 들어 ‘make deffernce’에서 사내아이디어 콘테스트
회의의 회의 코스트를 가시화 하여 효율화를 하고 시픔. 이거 실제 하고 있음
이 사진은 요코하마 연구소 오픈랩
고객과 이용 가능한 랩. 일본 전체 워크스타일 변혁을 위한 큰 흐름을 만들기를 생각 하고 있음
일본뿐 아니라 이노베이션을 위한 글로발적인 인재를 채용/육성을 하고자 함
미국실리콘밸리에서는 블럭체인/핀테크를 위한 랩, 고객과 금융 Co-Creation을 위한 금융이노베이션 랩
루마다 솔루션 개발을 위한 인사이트랩을 설치해 두고 잇음
이 거점에서 히다찌 사회이노베이션의 생각에 큰 공감을 해 준 실리콘밸리의 최첨단의 롯스터탤렌트가 결집함.
2017년 9월에 종래 스토리지 판매 HDS가 글로벌에 디지털 솔루션 제공하는 밴다로로 태어남
9월에 파트너이벤트에서 밴타라를 제창하고 글로발 IoT 파트너가 되도록 선언 함.
세계중의 과제를 디지털로 해결 하기 위해…
지속 가능한 사회를 어떻게 구현할까
7월 고배 의료 산업에
재생의료 스마트셀 인더스리ㅔ 오픈 이노베이션
일본 처음 패니실린 제조한 것은 히다찌가 납품한 것
70년넘은 노하우 축적
의학 사이버 바이오 반도체
무균성 사이버 자동 치료기 등
의료용도 안전 제공. 재생의료 보급에 공헌
정리하면
사회 이노베이션에서 목표로 하는 세계와. 많은 이해관계자와의 가치 평가에 대하여 소개 함
디지털화로 다양한 가치가 연결되고 사람들이 안전/안심/쾌적하게 살 수 있는 지속가능한 사회
히다찌는 OT/IT 플러덕 시스템 뿐 아니라 이런 사회 실현을 위한 디지털기술로 Co-Creation하는 인재가
준비되어 있다고 자부 합니다.
세계 변혁을 리드하는 새로운 미래를 만들기 위해서는 여러분의 힘이 필요합니다.
여러분과의 Co-Creation으로 많은 아이디어로 결집하여 사회이노베이션의 혁신을 리드
이것이 세계 큰 SD냔 일본5.0 이 련결된다고 확신