South and Southeast Asia is one of the major agricultural hubs of the world, facing challenges to feed the fast-growing population. Unpredictable climate change, land use crisis, soil quality degradation, frequent disasters related to water, labor shortages, and adaptation behavior are the major problems to maintain the optimum yield production. To solve the crisis, a transboundary approaches including IoT and AI are required to initiate in the field of agricultural machinery for addressing labor shortages, supply-chain logistics to minimize post-harvest losses, early warning to reduce damages in disaster and yield prediction for inventory planning to drive the sustainability goal for feeding the major part of 9 billion population by 2050 (Society 5.0 SDG 1 &2). The aim of the session is to focus on the recent achievements, challenges and future research direction of IoT and AI in agriculture to ensure food security, environmental and energy security for taking into account for climate change, disasters prevention, and smart adaptive technologies to reduce labor shortages in agriculture for the South and Southeast Asia (Globally SDG 13).
Time Table
| 9:30 AM - 9:35 AM | Tofael Ahamed Preface |
|---|---|
| 9:35 AM - 9:45 AM | Enomae Toshiharu Chair and Professor Div. of Appropriate Technology and Sciences for SD Faculty of Life & Environmental Sciences University of Tsukuba Welcome Address |
| 9:45 AM - 10:00 AM | Kyosuke Nagata President University of Tsukuba President Greetings |
| 10:05 AM - 10:45 AM | KOIKE Toshio “Promoting Interdisciplinary and Transdisciplinary Studies by DIAS” |
|---|---|
| 10:45 AM - 11:25 AM | Sakae Sibusawa “AI and IoT (Soil Sensing and Vegetation)” |
| 11:25 AM - 12:05 PM | NANSEKI, Teruaki “Smart Agriculture: Current Reality and Future Prospects in Japan” |
| 12:10 PM - 1:20 PM | Lunch Break |
| 1:30 PM - 2:00 PM | Prasanta K. Kalita “Developing Management Strategies for a Sustainable Rice Production under Climate Change and Water Scarcity Scenarios” |
|---|---|
| 2:30 PM - 3:00 PM | Martin Anda “AI and IoT: Application in Urban Water Management” |
| 2:30 PM - 3:00 PM | Lilik Budi Prasetyo “Shifting from Visual to Digital Forest Classification for National Monitoring System based on Machine Learning” |
| 3:00 PM - 3:10 PM | Coffee Break |
| 3:10 PM - 3:35 PM | Md. Maminul Huq “IoT and Computer Programing (Bangladesh)” |
|---|---|
| 3:35 PM - 4:00 PM | Mohamad Rashid Shariff Smart Agriculture (Malaysia)” |
| 4:00 PM - 4:25 PM | Wanrat Abdullakasim “Trends in AI and IoT for Thailand’s Smart Agriculture” |
| 4:25 PM - 4:50 PM | Yu Hope “IoT and AI in Agriculture (Application and World-Wide Market Prediction)” |
| 4:50 PM - 5:00 PM | Ryozo Noguchi Associate Professor Faculty of Life & Environmental Sciences University of Tsukuba Thanks Note and Closing Remarks |
Moderator
| Tofael Ahamed | Associate Professor, Faculty of Life & Environmental Sciences, University of Tsukuba |
|---|
Speakers
- Toshio Koike
- Director, International Centre for Water Hazard and Risk Management (ICHARM), Public Works Research Institute (PWRI) & Professor Emeritus, The University of Tokyo Council Member, Science Council Japan, Cabinet Office
- Toshio Koike is Executive Director of International Centre for Water Hazard and Risk Management (ICHARM) under the auspices of UNESCO and Professor Emeritus of the University of Tokyo. He has chaired the River Council of Japan since 2015 and led discussions on important river-related matters to advise the Minister of Land, Infrastructure, Transport and Tourism of Japan. In his capacity as a Council Member of the Science Council of Japan, Cabinet Office, he has also helped to improve and develop various aspects of science nationwide since 2017 via the provision of policy recommendations to the government and the public. He received the Bachelor, Master, and Doctor of Engineering, in 1980, 1982, and 1985, respectively, from the University of Tokyo, Japan. He was at the University of Tokyo, as a research associate in 1985 and a lecturer from 1986 to 1987, and at the Nagaoka University of Technology, Japan as an associate professor from 1988 to 1999 and a professor in 1999. In 1999, he joined the Department of Civil Engineering, the University of Tokyo, where he held the position of Professor until 2017.
- "Promoting Interdisciplinary and Transdisciplinary Studies by DIAS"
The Japanese government supported the development of a data system called "Data Integration and Analysis System (DIAS)," as one of the national key projects promoted by the Council for Science and Technology Policy (CSTP) from 2006 to 2010. The second phase from 2011 to 2015 was completed and the third one is also ongoing. The essential aim for the DIAS, which consists of four data components including data injection, management, integration, and interoperability, is to create knowledge that would enable solutions to problems and generate socioeconomic benefits. DIAS has been tackling a large increase in the diversity and volume of data from observing the Earth. Dictionaries have been developing an ontology system for technical and geographical terms, and a metadata design has been completed according to international standards. The volume of data stored has exponentially increased. Previously, almost all of the large-volume data came from satellites, but model outputs occupy the largest volume of our data storage nowadays. In collaboration with scientific and technological groups, DIAS can accelerate data archiving by including data loading, quality checking, metadata registration, and our system data-searching capability is being enriched. DIAS also enables scientists to perform integrated and interdisciplinary research by collaborating between different disciplines and promote transdisciplinary studies.
- Shibusawa Sakae
- Professor Emeritus, Part-time Professor WISE Program Tokyo University of Agriculture and Technology, Japan & Council Member of Science Council of Japan
- Prof. Shibusawa is one of the frontier researchers of Japan for his outstanding contribution in precision agriculture. Prof. Shibusawa has been working for many national and international projects for more than 15 years, He was the project director of the water-saving system for advanced precision agriculture (WSSPA) funded by the JST. The project aimed to save water by implementing an integrated site-specific precision agriculture technology. The project also designed to reuse and recycle the water resources capable to resilience from climate vulnerability. Prof. Shibusawa received outstanding contribution award from CIGR, Award from the Japan Society for Bioenvironmental Engineering Academic for successful implementation of community-based precision agriculture.
- "AI and IoT (Soil Sensing and Vegetation"
The presentation will mention a digital farming strategy involving a bottom-up activity of community-based precision agriculture, an experience on precision management, and a top-down activity of ICT/IoT policy to agriculture. With the experiment and practice for the last decades in Japan, it was recognized the management involved four levels of knowledge in action. Level 1 was to describe the spatio-temporal variability of the fields, such as soil/elevation mapping, yield/quality mapping, disease/weeds/growth mapping, and then to recognize the evidence. Level 2 was to understand why the variability came out, with help of farmers’ experience, mush up of date and memorized the work history and the environmental conditions, moreover to analyze behind mechanisms, models and assumption of the apparent results of parameters. Level 3 was to make decisions in order to increase the throughputs, looking at increases in the yield/quality under regional constraints, and reducing the cost, or change the cropping system. Level 4 was the action and evaluation, such as to choose actions under the constraints of labor, machinery, etc. When the storyboard of precision management was put in to practice, a help of cyber-physical system came up with an idea.
- Teruaki Nanseki
- Professor Department of Agriculture and Resource Economics Faculty of Agriculture, Kyushu University, Japan & President of Japanese Society of Agricultural Informatics (JSAI)
- Professor Nanseki is a distinguished researcher in his field and specialization of developing theory, methods, and information systems in management of risk, information, and human resources for agriculture, food, bio-resources, and the environment. His research activities cover practices and contributions to real farms and support policy making as well as academic contributions. He has worked for the research institutes of the Ministry of Agriculture, Forestry and Fisheries as well as the National Agriculture and Food Research Organization for more than 20 years. Prof. Nanseki has also given his expert contribution to the Japan International Cooperation Agency’s international projects in developing innovative approaches worldwide; these activities covered technology transfer and rural development in various countries including Colombia, the Philippines, and Indonesia. Dr. Nanseki has received more ten academic prizes from many academic societies including the Society of Agricultural Informatics, Society of Farm Management, Society of Environmental Science, Society of Operations Research, and so on. He has also received the Minister's Award for being an outstanding researcher of the Ministry of Agriculture, Forestry, and Fisheries. He was a president of the Japanese Society of Farm Management from 2014 to 2016.
- "Smart Agriculture: Current Reality and Future Prospects in Japan"
Smart agriculture has become an important issue in agricultural policy in Japan and the world. The field covers digitizing agriculture and precision agriculture/farming. Therefore, it is timely and crucial to clarify the current reality of smart agriculture and its limitations. This can first be done based on the research outputs of several national projects. As is well known, rice farming is one of Japan’s major crops in terms of the use of agricultural resources such as water, land, and labor. In this talk, we provide examples in the field that mainly include data sensing of each paddy field of a whole farm, big data analysis of rice farming, and automation of farm operations including water management. The prospects of smart agriculture in future are then discussed in terms of their potential and limitations from a wider perspective, such as by considering other fields of agriculture. The impacts of smart agriculture technologies on real farms differ across sectors of agriculture. In dairy farming, many types of robots have already been commercialized for almost all farm operations including feeding, manure cleaning, and milking. Nearly complete automatic production is currently possible in dairy farming, in contrast to this, rice farming faces many difficulties.
- Prasanta Kalita
- Professor and Presidential Fellow of the University of Illinois System Department of Agricultural and Biological Engineering, University of Illinois at Urbana-Champaign, USA
- Dr. Prasanta Kalita is a professor of Agricultural and Biological Engineering, and the Presidential Fellow of the University of Illinois System. Dr. Kalita also served as a director of the Archer Daniels Midland Company (ADM) Institute for the Prevention of Postharvest Losses as well as Associate Dean for Academic Programs. He has served as co-investigator for innovative projects involving partnerships with institutions such as the Illinois Department of Transportation, the US Army Corp of Engineers, the United States Agency for International Development, and universities around the world. He is a fellow of the American Society of Agricultural and Biological Engineers (ASABE) and Indian Society for Agricultural Engineering (ISAE). Dr. Kalita is widely recognized for his excellence in teaching, research, and international engagement; he has worked extensively in educational development and capacity building, water resources, food production, and food security issues around the world.
- "Developing Management Strategies for a Sustainable Rice Production under Climate Change and Water Scarcity Scenarios"
Climate change predictions will have significant impact on crop production, and thus, will affect food and water security issues in many developing countries. Since rice is the primary food for about 60% of world population, a study was conducted to predict the changes in the (a) rice yield and phenological growth, and (b) irrigation water requirement for maintaining current yield level as well as a 60% increase in rice yield by 2050s as would be affected by climate change. This study used a well validated crop growth model DSSAT for a rice production system in the state of Bihar, India. Four Global Climate Models (GCM) were used for four climate change scenarios (RCP 2.6, RCP 4.5, RCP 6.0 and RCP 8.5) to predict rice yield. The projected changes in climatic variables were predicted for 2020-2059 and were compared to the baseline period (1980-2004). We investigated several strategies, such as conservation agriculture and reduction of post-harvest loss, to reduce the water requirement for producing 60% more rice by 2059. This information can help in planning for maximizing rice production by adopting strategies to decrease water requirement under similar geographic and food scarce conditions, where water availability would be severely impacted by climate change.
- Martin Anda
- Academic Chair of Environmental Engineering Murdoch University, Australia
- Dr. Martin Anda is an environmental engineer and expertise in integrated ecotechnology. Dr. Martin and his research team along with industry partners and collaborator have been working to develop carbon neutral settlements, recycled water systems for urban villages, low cost but effective sanitation solutions for developing countries and innovative new water supply systems for remote Aboriginal communities. Dr. Martin has successfully completed number of prototypes of scientific research approaches based on integrated eco-technology. The most recent one is the decision support tool for irrigation in urban villages. Dr Anda’s research has implemented by the Environmental Technology Centre and Remote Area Developments Group, which is linked to the Desert Knowledge Cooperative Research Centre, the Sustainable Tourism CRC, Environmental Biotechnology CRC and the Australian Housing and Urban Research Institute. Dr. Martin was awarded the WA Water Professional of Year in 2016 for his outstanding contributions related to water in Western Australia.
- "AI and IoT: Application in Urban Water Management"
AI and machine learning techniques have already demonstrated significant outcomes in various water industry applications such as water quality monitoring, chemical dosing, prioritizing active leakage detection areas, intelligent network optimization, and the prediction of water pipe failure. Can these techniques be extended from water utility operations into home and commercial water usage? The rapid rate of global development in ultrasonic, revenue grade advanced metering technology is allowing the emergence of a new cost-effective approach to smart urban water management. It can enable hybrid water systems – those utilizing alternative and non-potable water sources – to be accurately quantified in a continuous manner without meter fouling. This in turn paves the way for hybrid water systems to be utilized in urban water trading – a novel market-based approach to a specified band of water use to enable higher levels of water efficiency. Over 60 ultrasonic smart water meters were deployed in 2018-19 across 40 participating households within the City of Fremantle, Perth, Western Australia. The approach adopted for the water component of Renew Nexus integrates the smart metering of hybrid water systems, household participation and data analytics at the residential scale within the traditional centralized urban water network. The introduction of a reward credit system to those residents who actively save energy-intensive mains water and wastewater, whilst optimally managing aquifer recharge, can support localized, hybrid water sources at residential and community scale.
- Lilik Budi Prasetyo
- Professor, Department of Forest Resources Conservation & Ecotourism, IPB University, & Indonesia UT-Bogor MoU Coordinator
- Dr. Lilik Budi Prasetyo is a distinguished Professor and expert of GIS and remote sensing of Indonesia. Apart from his academic affiliation he had been worked for several renown national and international research organizations such as Southeast Asian Regional Centre for Tropical Biology (SEAMEO BIOTROP), UNDP, National Institute of Agro-Environmental Sciences (NIES) Japan, Japan International Cooperation Agency, Disney Foundation, Osaka Gas Foundation and International Exchange as an GIS and Remote Sensing expert. Prof. Lilik has also collaboration with Tokyo University and University of Helsinki. Currently Prof. Lilik is leading three international projects collaborated with University of Tsukuba, Ministry Forestry of Nepal, PPLH-IPB, People Republic of China and Japan Aerospace Exploration Agency (JAXA). These projects aimed to apply the cutting-edge technology of remote sensing for forest management.
- "Shifting from Visual to Digital Forest Classification for National Monitoring System based on Machine Learning"
Indonesia has tropical forests with diverse ecosystems ranges from mountainous forest to mangrove in the coastal area that is very rich in biodiversity. In addition, with a very high carbon stock, Indonesia's forests also have an important role in the global carbon cycle. At present the forests face very high pressures due to agricultural expansion and forest fires, and therefore a fast & accurate monitoring system is needed. National Forest monitoring system in Indonesia has been established since 1990 and the criticism of the system is done manually. Moreover, defining forests in visual classification is also not in accordance with the definition of forests submitted by Indonesia to the UNFCCC, taking into account the variable tree height, percentage of canopy cover (CC) and minimal area. The process of changing the monitoring system from manual to digital begins with preprocessing, including the most important step of topographic correction, followed by determining the percentage of CC. The topographic correction was done by correcting reflectance based on pixels illumination due to the difference in slope & aspect. The determination of the canopy cover was estimated by using the relationship between the Landsat 8 OLI satellite image reflectance with the canopy cover derived from the LIDAR points cloud. Ecosystem diversity causes the relationship between pixels reflectance and CC to be inappropriate if done with conventional regression, meanwhile Support Vector Regression (SVR) provided a better result.
- Md. Maminul Huq
- Professor & Dean Faculty of Science & Engineering, Pundra University of Science and Technology, Bangladesh
- Prof. Md. Maminul Huq is the Dean of the Faculty of Engineering and Computer Science of Pundra University of Science and Technology of Bangladesh. Earlier, Prof. Huq was affiliated with Bangladesh Agricultural University (BAU), one of the renowned agricultural University of Southeast Asia for more than 41 years. His excellency in teaching the young researchers and undergrad students and devoted commitment towards academic activities created a benchmark for inspiration to introduce computer programming and application in agriculture. Prof. Huq has been working as an expert computer programming and ICT for the national and international projects. He and his research team also trying to apply service-oriented application of remote sensing technology in agriculture in Bangladesh, a project funded by UNDP.
- "IoT and Computer Programing Prospects in Bangladesh"
In Bangladesh about 64% percent people are living in rural areas according to the World Bank. Among them around 48% are employed in the agricultural sector and a large majority of the rural population is involved in fisheries. It is proven that IoT is a highly promising technology and can able to offer many solutions related to crop, livestock and fisheries for marketing to consumptions. IoT can be advantageous for Bangladesh in different fields of agriculture such as shared irrigation, shared machinery utilization, pest control, livestock monitoring, in-house production, urban agriculture and agro-banking services. As IoT depends on “smart” things and network over which they can communicate through the strong telecommunications system. The telecommunication system enjoys the government support and affordable things easily. The low-cost Internet service got popularity through the extent mobile network system throughout the country. Application of IoT through cell phone services has the potential to increase job opportunity and encourage young entrepreneurs in the agricultural production and food industry.
- Abdul Rashid Bin Mohamed Shariff
- Professor Department of Biological and Agricultural Engineering University Putra Malaysia, Malaysia & UT-UPM MoU Coordinator
- Prof. Sr. Gs Dr. Abdul Rashid is a renowned expert with more than 20 years of experience in the field of Geographical Information System (GIS) and remote sensing. His contributions on Geographical Information Systems for Agriculture were included in the CIGR (International Commission of Agricultural and Biosystems Engineering) Handbook of Agricultural Engineering Volume VI: Information Technology. Prof Rashid Mohamed Shariff was one of the recipients of the award of Top Research Scientists Malaysia (TRSM) Awards in 2018. He has also received Gold Medal at Geneva’s Inventors Competition, and award for the best speaker in an international GIS and Remote Sensing conference. As a specialist in GIS, Dr. Rashid helps the expansion of GIS into Agriculture, Healthcare, and Environment with the innovative spatial analysis. Dr. Rashid has successfully lead national and international projects. He had worked for the Space Applications for Environment (SAFE) and contributed for the SAFE initiative of Asia-Pacific Regional Space Agency Forum (APRSAF). Dr. Rashid has published or co-authored about 200 articles in journals, conferences, workshops, invitational talks and technical reports.
- "IoSmart Agriculture in Malaysiah"
This presentations gives applications of Smart Agriculture using geospatial technologies. We demonstrate how the best land suited for a particular crop, taking into account the agro-climatic parameters, can be determined using the Agriculture Land Suitability Evaluator (ALSE). The synergy between GIS and information technology to produce a web based precision farming guide for semi-literate farmers is shown. This practical approach helps alleviate the skills of farmers and their children into the IT era. Method of nitrogen fertilizer management of oil palm from space using Spot 7 satellite image is explained. These are steps in the eventual automation of fertilizer applications and management in the palm oil industry. In tandem with current industry concerns and emphasis on harvesting the ripe oil palm bunches, we provide our approach using the optical, hyperspectral and fluorescence approaches. As plantations naturally attract pests in a healthy environment, one of which is the bagworm, we present our method which is a basis to develop an automated detector and counter for bagworm census. The overall research presented in this lecture will be beneficial to the researchers and practitioners, and with people interested in geospatial agriculture technology.
- Wanrat Abdullakasim
- Assistant Professor Department of Agricultural Engineering, & Associate Dean for International Affairs Kasetsart University, Thailand
- Dr. Wanrat is an expert in field of pre-harvest machinery and precision agriculture. The majority of his research is focused on field crops mechanization technology, specifically for cassava and sugarcane production. He has applied different techniques of image analysis to detect and assess the severity of cassava diseases. He uses unmanned aerial vehicles (UAVs) with developed low-cost sensing devices for crop growth monitoring and yield prediction. Currently, Dr. Wanrat and his research team are conducting a study on cassava and sugarcane responses to salt stress and water deficit using hyperspectral imaging technique. Dr. Wanrat also serves his faculty as Associate Dean for International Affairs. He collaborates with national and international universities to promote student mobility and new pedagogy for outcome-based learning. Dr. Wanrat is a member of academic board of the Thai Society of Agricultural Engineering (TSAE), and a member of the International Society for Southeast Asian Agricultural Sciences (ISSAAS).
- "Trends in AI and IoT for Thailand’s Smart Agriculture"
Agriculture and biotechnology have been ranked as an “Engine of Growth” in Thailand’s economic roadmap. Development of smart agriculture and smart farmers therefore becomes an important agenda in the national strategic plan. This vision has successfully attracted the private sector to increase their investment in smart agriculture technology, especially by the young entrepreneurs that obviously interesting to launch their startup business related to smart farm. National agencies and universities play substantial roles in conducting applied research on AI and IoT as well as promoting co-creation environment between innovators for the benefit of resource sharing and exchange. At present, Thailand is in the stage of developing technology platform for agricultural big data collection, e.g. ambient sensing system for plantation sites and greenhouses, 3D farming robots, intelligent growth chamber, camera with embedded pattern recognition, and plant phenotyping systems, which has been applying to rice, corn, sugarcane, cassava, and fruits and vegetables. A non-contact intelligent plant factory has been developed, targeted for pharmaceutical plants such as, recently, marijuana, and high-value seeds production. Regarding which, telecommunication companies and internet service providers are key players in connecting those systems into the IoT. Capacity building on data science is meanwhile intensively carried out for every level of people. In conclusion, AI and IoT is believed to be a key technology for future Thailand agriculture that emerges new business models with satisfactory subsequent outcomes.
- Yu Hope
- President & CEOCompanies: i-focus Co., Ltd. & Clevagri Co., Ltd. Clevagri Biz. Contents: IoT, AI, and Cloud Solution for Smart Agriculturei-focus Biz. Contents: Whole Solutions on AI, IoT, and Cloud Expertise in AI, IoT & Cloud Solutions,Expertise in Bank System Architecture Design and Development, Framework Design and Development
- Mr. Yu is currently for the president and CEO of both companies of i-focus Co., Ltd. and Clevagri Co., Ltd., doing his best in supporting Japan’s agriculture by developing systems and solutions with techniques of AI, IoT, and Cloud. Mr. Yu graduated from China’s top-class technology university of Haerbin Institute of Technology (HIT, CHINA), majoring in Material Science, which is one of university’s strongest research areas. Later, Mr. Yu mainly worked in the areas of System Design and Development, achieved his excellent expertise in Bank System Architecture Design and Development and Framework Building areas. His working experience in Developing Watson’s AI Platform in cooperation with IBM team, makes him an elite specialist in AI System Design and Development area, also is the reason that Mr. Yu is now also a Cloud &IoT Solutions consultant for several companies such as Softbank, SBCloud, etc.
- "IoT and AI in Agriculture (Application and World-Wide Market Prediction"
The Internet of Things (IoT) triumphally changes the world. In fact, it has already introduced innovation in various industries, which assisted in increasing the effectiveness and cutting the costs of business operations in different aspects. And the area of agriculture fits this trend totally. Machine learning is performed using data collected from various sensors using the IoT platform, and an AI engine is built to support development of agriculture sector. And so, it is possible to discuss agriculture IoT as the whole sphere. To address this task, we discover the main directions in which Internet of Things (IoT) applications in agriculture managed to make a significant impact. Utilizing image analysis and neural network technology, scientific growth evaluation and growth scenario optimization will contribute to quality improvement. Our company main tasks green house crop cultivation monitoring which monitor data from sensors in real time and check the cultivation status anytime, anywhere, Remote control system is an automatic control based on sender data and production planning and work management we can centrally manage from cultivation plan to work management
南アジアと東南アジアは、世界の主要な食料生産拠点である一方で、経済の急成長による人口増加、食料増産の課題に直面している。予測不可能な気候変動、農業のための土地利用の危機的状況、土壌性質の悪化、頻繁な水害、労働力不足、適応行動の欠如が、十分な収量を維持するための食料生産において、大きな課題となっている。2050年までに90億人の人口を養うための持続可能性の目標を推進（Society 5.0 SDG 1＆2）の観点からも、これらの危機的課題を解決するためには、国境を越えたIoTとAIによる農業への技術的アプローチは、 労働力不足や収穫後の損失を最小限に抑えるためのサプライチェーンロジスティクス、災害による損失を軽減するための早期警戒システム、食料在庫計画のための収穫量予測への取り組みが必要となる。本セッションの目的は、南アジアと東南アジアにおける食料不足への対応（SDG 13）に対して、農業におけるIoTとAIを応用した食料生産に関する成果や課題、将来の研究の方向性に焦点を絞り、気候変動を考慮した食料安全保障、環境とエネルギーの確保、災害防止、および労働力不足を補うためのスマート適応技術について議論を行うことにある。
Time Table
| 9:30 AM - 9:35 AM | Tofael Ahamed Preface |
|---|---|
| 9:35 AM - 9:45 AM | Enomae Toshiharu Chair and Professor Div. of Appropriate Technology and Sciences for SD Faculty of Life & Environmental Sciences University of Tsukuba Welcome Address |
| 9:45 AM - 10:00 AM | Kyosuke Nagata President University of Tsukuba President Greetings |
| 10:05 AM - 10:45 AM | KOIKE Toshio “Promoting Interdisciplinary and Transdisciplinary Studies by DIAS” |
|---|---|
| 10:45 AM - 11:25 AM | Sakae Sibusawa “AI and IoT (Soil Sensing and Vegetation)” |
| 11:25 AM - 12:05 PM | NANSEKI, Teruaki “Smart Agriculture: Current Reality and Future Prospects in Japan” |
| 12:10 PM - 1:20 PM | Lunch Break |
| 1:30 PM - 2:00 PM | Prasanta K. Kalita “Developing Management Strategies for a Sustainable Rice Production under Climate Change and Water Scarcity Scenarios” |
|---|---|
| 2:30 PM - 3:00 PM | Martin Anda “AI and IoT: Application in Urban Water Management” |
| 2:30 PM - 3:00 PM | Lilik Budi Prasetyo “Shifting from Visual to Digital Forest Classification for National Monitoring System based on Machine Learning” |
| 3:00 PM - 3:10 PM | Coffee Break |
| 3:10 PM - 3:35 PM | Md. Maminul Huq “IoT and Computer Programing (Bangladesh)” |
|---|---|
| 3:35 PM - 4:00 PM | Mohamad Rashid Shariff Smart Agriculture (Malaysia)” |
| 4:00 PM - 4:25 PM | Wanrat Abdullakasim “Trends in AI and IoT for Thailand’s Smart Agriculture” |
| 4:25 PM - 4:50 PM | Yu Hope “IoT and AI in Agriculture (Application and World-Wide Market Prediction)” |
| 4:50 PM - 5:00 PM | Ryozo Noguchi Associate Professor Faculty of Life & Environmental Sciences University of Tsukuba Thanks Note and Closing Remarks |
Moderator
| Tofael Ahamed | Associate Professor, Faculty of Life & Environmental Sciences, University of Tsukuba |
|---|
Speakers
- Toshio Koike
- Director, International Centre for Water Hazard and Risk Management (ICHARM), Public Works Research Institute (PWRI) & Professor Emeritus, The University of Tokyo Council Member, Science Council Japan, Cabinet Office
- Toshio Koike is Executive Director of International Centre for Water Hazard and Risk Management (ICHARM) under the auspices of UNESCO and Professor Emeritus of the University of Tokyo. He has chaired the River Council of Japan since 2015 and led discussions on important river-related matters to advise the Minister of Land, Infrastructure, Transport and Tourism of Japan. In his capacity as a Council Member of the Science Council of Japan, Cabinet Office, he has also helped to improve and develop various aspects of science nationwide since 2017 via the provision of policy recommendations to the government and the public. He received the Bachelor, Master, and Doctor of Engineering, in 1980, 1982, and 1985, respectively, from the University of Tokyo, Japan. He was at the University of Tokyo, as a research associate in 1985 and a lecturer from 1986 to 1987, and at the Nagaoka University of Technology, Japan as an associate professor from 1988 to 1999 and a professor in 1999. In 1999, he joined the Department of Civil Engineering, the University of Tokyo, where he held the position of Professor until 2017.
- "Promoting Interdisciplinary and Transdisciplinary Studies by DIAS"
The Japanese government supported the development of a data system called "Data Integration and Analysis System (DIAS)," as one of the national key projects promoted by the Council for Science and Technology Policy (CSTP) from 2006 to 2010. The second phase from 2011 to 2015 was completed and the third one is also ongoing. The essential aim for the DIAS, which consists of four data components including data injection, management, integration, and interoperability, is to create knowledge that would enable solutions to problems and generate socioeconomic benefits. DIAS has been tackling a large increase in the diversity and volume of data from observing the Earth. Dictionaries have been developing an ontology system for technical and geographical terms, and a metadata design has been completed according to international standards. The volume of data stored has exponentially increased. Previously, almost all of the large-volume data came from satellites, but model outputs occupy the largest volume of our data storage nowadays. In collaboration with scientific and technological groups, DIAS can accelerate data archiving by including data loading, quality checking, metadata registration, and our system data-searching capability is being enriched. DIAS also enables scientists to perform integrated and interdisciplinary research by collaborating between different disciplines and promote transdisciplinary studies.
- Shibusawa Sakae
- Professor Emeritus, Part-time Professor WISE Program Tokyo University of Agriculture and Technology, Japan & Council Member of Science Council of Japan
- Prof. Shibusawa is one of the frontier researchers of Japan for his outstanding contribution in precision agriculture. Prof. Shibusawa has been working for many national and international projects for more than 15 years, He was the project director of the water-saving system for advanced precision agriculture (WSSPA) funded by the JST. The project aimed to save water by implementing an integrated site-specific precision agriculture technology. The project also designed to reuse and recycle the water resources capable to resilience from climate vulnerability. Prof. Shibusawa received outstanding contribution award from CIGR, Award from the Japan Society for Bioenvironmental Engineering Academic for successful implementation of community-based precision agriculture.
- "AI and IoT (Soil Sensing and Vegetation"
The presentation will mention a digital farming strategy involving a bottom-up activity of community-based precision agriculture, an experience on precision management, and a top-down activity of ICT/IoT policy to agriculture. With the experiment and practice for the last decades in Japan, it was recognized the management involved four levels of knowledge in action. Level 1 was to describe the spatio-temporal variability of the fields, such as soil/elevation mapping, yield/quality mapping, disease/weeds/growth mapping, and then to recognize the evidence. Level 2 was to understand why the variability came out, with help of farmers’ experience, mush up of date and memorized the work history and the environmental conditions, moreover to analyze behind mechanisms, models and assumption of the apparent results of parameters. Level 3 was to make decisions in order to increase the throughputs, looking at increases in the yield/quality under regional constraints, and reducing the cost, or change the cropping system. Level 4 was the action and evaluation, such as to choose actions under the constraints of labor, machinery, etc. When the storyboard of precision management was put in to practice, a help of cyber-physical system came up with an idea.
- Teruaki Nanseki
- Professor Department of Agriculture and Resource Economics Faculty of Agriculture, Kyushu University, Japan & President of Japanese Society of Agricultural Informatics (JSAI)
- Professor Nanseki is a distinguished researcher in his field and specialization of developing theory, methods, and information systems in management of risk, information, and human resources for agriculture, food, bio-resources, and the environment. His research activities cover practices and contributions to real farms and support policy making as well as academic contributions. He has worked for the research institutes of the Ministry of Agriculture, Forestry and Fisheries as well as the National Agriculture and Food Research Organization for more than 20 years. Prof. Nanseki has also given his expert contribution to the Japan International Cooperation Agency’s international projects in developing innovative approaches worldwide; these activities covered technology transfer and rural development in various countries including Colombia, the Philippines, and Indonesia. Dr. Nanseki has received more ten academic prizes from many academic societies including the Society of Agricultural Informatics, Society of Farm Management, Society of Environmental Science, Society of Operations Research, and so on. He has also received the Minister's Award for being an outstanding researcher of the Ministry of Agriculture, Forestry, and Fisheries. He was a president of the Japanese Society of Farm Management from 2014 to 2016.
- "Smart Agriculture: Current Reality and Future Prospects in Japan"
Smart agriculture has become an important issue in agricultural policy in Japan and the world. The field covers digitizing agriculture and precision agriculture/farming. Therefore, it is timely and crucial to clarify the current reality of smart agriculture and its limitations. This can first be done based on the research outputs of several national projects. As is well known, rice farming is one of Japan’s major crops in terms of the use of agricultural resources such as water, land, and labor. In this talk, we provide examples in the field that mainly include data sensing of each paddy field of a whole farm, big data analysis of rice farming, and automation of farm operations including water management. The prospects of smart agriculture in future are then discussed in terms of their potential and limitations from a wider perspective, such as by considering other fields of agriculture. The impacts of smart agriculture technologies on real farms differ across sectors of agriculture. In dairy farming, many types of robots have already been commercialized for almost all farm operations including feeding, manure cleaning, and milking. Nearly complete automatic production is currently possible in dairy farming, in contrast to this, rice farming faces many difficulties.
- Prasanta Kalita
- Professor and Presidential Fellow of the University of Illinois System Department of Agricultural and Biological Engineering, University of Illinois at Urbana-Champaign, USA
- Dr. Prasanta Kalita is a professor of Agricultural and Biological Engineering, and the Presidential Fellow of the University of Illinois System. Dr. Kalita also served as a director of the Archer Daniels Midland Company (ADM) Institute for the Prevention of Postharvest Losses as well as Associate Dean for Academic Programs. He has served as co-investigator for innovative projects involving partnerships with institutions such as the Illinois Department of Transportation, the US Army Corp of Engineers, the United States Agency for International Development, and universities around the world. He is a fellow of the American Society of Agricultural and Biological Engineers (ASABE) and Indian Society for Agricultural Engineering (ISAE). Dr. Kalita is widely recognized for his excellence in teaching, research, and international engagement; he has worked extensively in educational development and capacity building, water resources, food production, and food security issues around the world.
- "Developing Management Strategies for a Sustainable Rice Production under Climate Change and Water Scarcity Scenarios"
Climate change predictions will have significant impact on crop production, and thus, will affect food and water security issues in many developing countries. Since rice is the primary food for about 60% of world population, a study was conducted to predict the changes in the (a) rice yield and phenological growth, and (b) irrigation water requirement for maintaining current yield level as well as a 60% increase in rice yield by 2050s as would be affected by climate change. This study used a well validated crop growth model DSSAT for a rice production system in the state of Bihar, India. Four Global Climate Models (GCM) were used for four climate change scenarios (RCP 2.6, RCP 4.5, RCP 6.0 and RCP 8.5) to predict rice yield. The projected changes in climatic variables were predicted for 2020-2059 and were compared to the baseline period (1980-2004). We investigated several strategies, such as conservation agriculture and reduction of post-harvest loss, to reduce the water requirement for producing 60% more rice by 2059. This information can help in planning for maximizing rice production by adopting strategies to decrease water requirement under similar geographic and food scarce conditions, where water availability would be severely impacted by climate change.
- Martin Anda
- Academic Chair of Environmental Engineering Murdoch University, Australia
- Dr. Martin Anda is an environmental engineer and expertise in integrated ecotechnology. Dr. Martin and his research team along with industry partners and collaborator have been working to develop carbon neutral settlements, recycled water systems for urban villages, low cost but effective sanitation solutions for developing countries and innovative new water supply systems for remote Aboriginal communities. Dr. Martin has successfully completed number of prototypes of scientific research approaches based on integrated eco-technology. The most recent one is the decision support tool for irrigation in urban villages. Dr Anda’s research has implemented by the Environmental Technology Centre and Remote Area Developments Group, which is linked to the Desert Knowledge Cooperative Research Centre, the Sustainable Tourism CRC, Environmental Biotechnology CRC and the Australian Housing and Urban Research Institute. Dr. Martin was awarded the WA Water Professional of Year in 2016 for his outstanding contributions related to water in Western Australia.
- "AI and IoT: Application in Urban Water Management"
AI and machine learning techniques have already demonstrated significant outcomes in various water industry applications such as water quality monitoring, chemical dosing, prioritizing active leakage detection areas, intelligent network optimization, and the prediction of water pipe failure. Can these techniques be extended from water utility operations into home and commercial water usage? The rapid rate of global development in ultrasonic, revenue grade advanced metering technology is allowing the emergence of a new cost-effective approach to smart urban water management. It can enable hybrid water systems – those utilizing alternative and non-potable water sources – to be accurately quantified in a continuous manner without meter fouling. This in turn paves the way for hybrid water systems to be utilized in urban water trading – a novel market-based approach to a specified band of water use to enable higher levels of water efficiency. Over 60 ultrasonic smart water meters were deployed in 2018-19 across 40 participating households within the City of Fremantle, Perth, Western Australia. The approach adopted for the water component of Renew Nexus integrates the smart metering of hybrid water systems, household participation and data analytics at the residential scale within the traditional centralized urban water network. The introduction of a reward credit system to those residents who actively save energy-intensive mains water and wastewater, whilst optimally managing aquifer recharge, can support localized, hybrid water sources at residential and community scale.
- Lilik Budi Prasetyo
- Professor, Department of Forest Resources Conservation & Ecotourism, IPB University, & Indonesia UT-Bogor MoU Coordinator
- Dr. Lilik Budi Prasetyo is a distinguished Professor and expert of GIS and remote sensing of Indonesia. Apart from his academic affiliation he had been worked for several renown national and international research organizations such as Southeast Asian Regional Centre for Tropical Biology (SEAMEO BIOTROP), UNDP, National Institute of Agro-Environmental Sciences (NIES) Japan, Japan International Cooperation Agency, Disney Foundation, Osaka Gas Foundation and International Exchange as an GIS and Remote Sensing expert. Prof. Lilik has also collaboration with Tokyo University and University of Helsinki. Currently Prof. Lilik is leading three international projects collaborated with University of Tsukuba, Ministry Forestry of Nepal, PPLH-IPB, People Republic of China and Japan Aerospace Exploration Agency (JAXA). These projects aimed to apply the cutting-edge technology of remote sensing for forest management.
- "Shifting from Visual to Digital Forest Classification for National Monitoring System based on Machine Learning"
Indonesia has tropical forests with diverse ecosystems ranges from mountainous forest to mangrove in the coastal area that is very rich in biodiversity. In addition, with a very high carbon stock, Indonesia's forests also have an important role in the global carbon cycle. At present the forests face very high pressures due to agricultural expansion and forest fires, and therefore a fast & accurate monitoring system is needed. National Forest monitoring system in Indonesia has been established since 1990 and the criticism of the system is done manually. Moreover, defining forests in visual classification is also not in accordance with the definition of forests submitted by Indonesia to the UNFCCC, taking into account the variable tree height, percentage of canopy cover (CC) and minimal area. The process of changing the monitoring system from manual to digital begins with preprocessing, including the most important step of topographic correction, followed by determining the percentage of CC. The topographic correction was done by correcting reflectance based on pixels illumination due to the difference in slope & aspect. The determination of the canopy cover was estimated by using the relationship between the Landsat 8 OLI satellite image reflectance with the canopy cover derived from the LIDAR points cloud. Ecosystem diversity causes the relationship between pixels reflectance and CC to be inappropriate if done with conventional regression, meanwhile Support Vector Regression (SVR) provided a better result.
- Md. Maminul Huq
- Professor & Dean Faculty of Science & Engineering, Pundra University of Science and Technology, Bangladesh
- Prof. Md. Maminul Huq is the Dean of the Faculty of Engineering and Computer Science of Pundra University of Science and Technology of Bangladesh. Earlier, Prof. Huq was affiliated with Bangladesh Agricultural University (BAU), one of the renowned agricultural University of Southeast Asia for more than 41 years. His excellency in teaching the young researchers and undergrad students and devoted commitment towards academic activities created a benchmark for inspiration to introduce computer programming and application in agriculture. Prof. Huq has been working as an expert computer programming and ICT for the national and international projects. He and his research team also trying to apply service-oriented application of remote sensing technology in agriculture in Bangladesh, a project funded by UNDP.
- "IoT and Computer Programing Prospects in Bangladesh"
In Bangladesh about 64% percent people are living in rural areas according to the World Bank. Among them around 48% are employed in the agricultural sector and a large majority of the rural population is involved in fisheries. It is proven that IoT is a highly promising technology and can able to offer many solutions related to crop, livestock and fisheries for marketing to consumptions. IoT can be advantageous for Bangladesh in different fields of agriculture such as shared irrigation, shared machinery utilization, pest control, livestock monitoring, in-house production, urban agriculture and agro-banking services. As IoT depends on “smart” things and network over which they can communicate through the strong telecommunications system. The telecommunication system enjoys the government support and affordable things easily. The low-cost Internet service got popularity through the extent mobile network system throughout the country. Application of IoT through cell phone services has the potential to increase job opportunity and encourage young entrepreneurs in the agricultural production and food industry.
- Abdul Rashid Bin Mohamed Shariff
- Professor Department of Biological and Agricultural Engineering University Putra Malaysia, Malaysia & UT-UPM MoU Coordinator
- Prof. Sr. Gs Dr. Abdul Rashid is a renowned expert with more than 20 years of experience in the field of Geographical Information System (GIS) and remote sensing. His contributions on Geographical Information Systems for Agriculture were included in the CIGR (International Commission of Agricultural and Biosystems Engineering) Handbook of Agricultural Engineering Volume VI: Information Technology. Prof Rashid Mohamed Shariff was one of the recipients of the award of Top Research Scientists Malaysia (TRSM) Awards in 2018. He has also received Gold Medal at Geneva’s Inventors Competition, and award for the best speaker in an international GIS and Remote Sensing conference. As a specialist in GIS, Dr. Rashid helps the expansion of GIS into Agriculture, Healthcare, and Environment with the innovative spatial analysis. Dr. Rashid has successfully lead national and international projects. He had worked for the Space Applications for Environment (SAFE) and contributed for the SAFE initiative of Asia-Pacific Regional Space Agency Forum (APRSAF). Dr. Rashid has published or co-authored about 200 articles in journals, conferences, workshops, invitational talks and technical reports.
- "IoSmart Agriculture in Malaysiah"
This presentations gives applications of Smart Agriculture using geospatial technologies. We demonstrate how the best land suited for a particular crop, taking into account the agro-climatic parameters, can be determined using the Agriculture Land Suitability Evaluator (ALSE). The synergy between GIS and information technology to produce a web based precision farming guide for semi-literate farmers is shown. This practical approach helps alleviate the skills of farmers and their children into the IT era. Method of nitrogen fertilizer management of oil palm from space using Spot 7 satellite image is explained. These are steps in the eventual automation of fertilizer applications and management in the palm oil industry. In tandem with current industry concerns and emphasis on harvesting the ripe oil palm bunches, we provide our approach using the optical, hyperspectral and fluorescence approaches. As plantations naturally attract pests in a healthy environment, one of which is the bagworm, we present our method which is a basis to develop an automated detector and counter for bagworm census. The overall research presented in this lecture will be beneficial to the researchers and practitioners, and with people interested in geospatial agriculture technology.
- Wanrat Abdullakasim
- Assistant Professor Department of Agricultural Engineering, & Associate Dean for International Affairs Kasetsart University, Thailand
- Dr. Wanrat is an expert in field of pre-harvest machinery and precision agriculture. The majority of his research is focused on field crops mechanization technology, specifically for cassava and sugarcane production. He has applied different techniques of image analysis to detect and assess the severity of cassava diseases. He uses unmanned aerial vehicles (UAVs) with developed low-cost sensing devices for crop growth monitoring and yield prediction. Currently, Dr. Wanrat and his research team are conducting a study on cassava and sugarcane responses to salt stress and water deficit using hyperspectral imaging technique. Dr. Wanrat also serves his faculty as Associate Dean for International Affairs. He collaborates with national and international universities to promote student mobility and new pedagogy for outcome-based learning. Dr. Wanrat is a member of academic board of the Thai Society of Agricultural Engineering (TSAE), and a member of the International Society for Southeast Asian Agricultural Sciences (ISSAAS).
- "Trends in AI and IoT for Thailand’s Smart Agriculture"
Agriculture and biotechnology have been ranked as an “Engine of Growth” in Thailand’s economic roadmap. Development of smart agriculture and smart farmers therefore becomes an important agenda in the national strategic plan. This vision has successfully attracted the private sector to increase their investment in smart agriculture technology, especially by the young entrepreneurs that obviously interesting to launch their startup business related to smart farm. National agencies and universities play substantial roles in conducting applied research on AI and IoT as well as promoting co-creation environment between innovators for the benefit of resource sharing and exchange. At present, Thailand is in the stage of developing technology platform for agricultural big data collection, e.g. ambient sensing system for plantation sites and greenhouses, 3D farming robots, intelligent growth chamber, camera with embedded pattern recognition, and plant phenotyping systems, which has been applying to rice, corn, sugarcane, cassava, and fruits and vegetables. A non-contact intelligent plant factory has been developed, targeted for pharmaceutical plants such as, recently, marijuana, and high-value seeds production. Regarding which, telecommunication companies and internet service providers are key players in connecting those systems into the IoT. Capacity building on data science is meanwhile intensively carried out for every level of people. In conclusion, AI and IoT is believed to be a key technology for future Thailand agriculture that emerges new business models with satisfactory subsequent outcomes.
- Yu Hope
- President & CEOCompanies: i-focus Co., Ltd. & Clevagri Co., Ltd. Clevagri Biz. Contents: IoT, AI, and Cloud Solution for Smart Agriculturei-focus Biz. Contents: Whole Solutions on AI, IoT, and Cloud Expertise in AI, IoT & Cloud Solutions,Expertise in Bank System Architecture Design and Development, Framework Design and Development
- Mr. Yu is currently for the president and CEO of both companies of i-focus Co., Ltd. and Clevagri Co., Ltd., doing his best in supporting Japan’s agriculture by developing systems and solutions with techniques of AI, IoT, and Cloud. Mr. Yu graduated from China’s top-class technology university of Haerbin Institute of Technology (HIT, CHINA), majoring in Material Science, which is one of university’s strongest research areas. Later, Mr. Yu mainly worked in the areas of System Design and Development, achieved his excellent expertise in Bank System Architecture Design and Development and Framework Building areas. His working experience in Developing Watson’s AI Platform in cooperation with IBM team, makes him an elite specialist in AI System Design and Development area, also is the reason that Mr. Yu is now also a Cloud &IoT Solutions consultant for several companies such as Softbank, SBCloud, etc.
- "IoT and AI in Agriculture (Application and World-Wide Market Prediction"
The Internet of Things (IoT) triumphally changes the world. In fact, it has already introduced innovation in various industries, which assisted in increasing the effectiveness and cutting the costs of business operations in different aspects. And the area of agriculture fits this trend totally. Machine learning is performed using data collected from various sensors using the IoT platform, and an AI engine is built to support development of agriculture sector. And so, it is possible to discuss agriculture IoT as the whole sphere. To address this task, we discover the main directions in which Internet of Things (IoT) applications in agriculture managed to make a significant impact. Utilizing image analysis and neural network technology, scientific growth evaluation and growth scenario optimization will contribute to quality improvement. Our company main tasks green house crop cultivation monitoring which monitor data from sensors in real time and check the cultivation status anytime, anywhere, Remote control system is an automatic control based on sender data and production planning and work management we can centrally manage from cultivation plan to work management