2 research outputs found

    Self-Deployable Indoor Localization With Acoustic-Enabled IoT Devices Exploiting Participatory Sensing

    No full text

    Data-Driven System Analysis for Regional Issues

    Get PDF
    ν•™μœ„λ…Όλ¬Έ(박사) -- μ„œμšΈλŒ€ν•™κ΅λŒ€ν•™μ› : 농업생λͺ…κ³Όν•™λŒ€ν•™ ν˜‘λ™κ³Όμ • 농림기상학, 2021.8. μ„œκ΅.4μ°¨ μ‚°μ—…ν˜λͺ… μ‹œλŒ€ κΈ°μˆ λ°œμ „μ˜ μ€‘μ‹¬μ—λŠ” 데이터가 μžˆλ‹€. λ°μ΄ν„°λŠ” 맀년 μ–‘(Volume), λ‹€μ–‘μ„±(Variety), 속도(Velocity) λ“±μ˜ μΈ‘λ©΄μ—μ„œ 폭발적으둜 μ„±μž₯ν•˜λ©° μ¦κ°€ν•˜λ©΄μ„œ ν˜μ‹ μ  기술의 기반이 되고 μžˆλ‹€. 특히, μ΄λŸ¬ν•œ λ°μ΄ν„°λŠ” μ§€μ‹μ •λ³΄κΈ°μˆ μ˜ λ°œλ‹¬μ„ 톡해 λ‹€μ–‘ν•œ λΆ„μ•Όμ—μ„œ λ¬Έμ œν•΄κ²°μ„ μœ„ν•œ μ˜μ‚¬κ²°μ •μ΄λ‚˜ μ •μ±… μˆ˜λ¦½μ— μžˆμ–΄μ„œ 졜적의 λŒ€μ•ˆμ„ μ°ΎκΈ° μœ„ν•œ 효과적인 방법에도 κ·Έ ν™œμš©μ„±μ΄ λΆ€κ°λ˜κ³  μžˆλ‹€. 데이터 μ‚¬μ΄μ–ΈμŠ€λŠ” μ΄λŸ¬ν•œ λ°μ΄ν„°μ˜ ν˜μ‹ μ μΈ 증가와 μ„±μž₯을 기반으둜 λ‹€μ–‘ν•œ ν˜•νƒœμ˜ μ‹œμŠ€ν…œμ΄ λ‹Ήλ©΄ν•œ 문제λ₯Ό μ •ν™•νžˆ μΈμ‹ν•˜κ³  이λ₯Ό ν•΄κ²°ν•  수 μžˆλŠ” 핡심 데이터λ₯Ό νŒŒμ•…ν•˜μ—¬, μ ν•©ν•œ 뢄석기법을 톡해 λ¬Έμ œμ— λŒ€ν•œ 해법을 λ„μΆœν•˜λŠ” λΆ„μ•Όλ‘œ μ£Όλͺ©λ°›κ³  μžˆλ‹€. λ†μ—…λ†μ΄Œ λΆ„μ•Όμ—μ„œλŠ” λ†μ΄Œμ΄ λ‹Ήλ©΄ν•œ 인ꡬ κ°μ†Œ, κ³ λ Ήν™”, 곡동화 λ“± μ—΄μ•…ν•œ ν™˜κ²½μ—μ„œ ν•œμ •λœ μžμ›μ„ μœ νš¨ν•˜κ²Œ ν™œμš©ν•˜λ©΄μ„œ μ§€μ—­μ˜ νŠΉμ„±μ„ κ³ λ €ν•˜μ—¬ 문제λ₯Ό ν•΄κ²°ν•  수 μžˆλŠ” μ •λŸ‰μ μΈ λ°©μ•ˆμ„ λ„μΆœν•˜κ³  κ·Έ 효과λ₯Ό κ²€μ¦ν•˜λŠ” λ°©μ•ˆμ„ λͺ¨μƒ‰ν•˜κ³  μžˆλ‹€. 이λ₯Ό μœ„ν•΄ λ†μ΄Œμ˜ λ‹€μ–‘ν•œ ν˜„μ•ˆλ“€μ— λŒ€ν•œ μˆ˜μš”λ₯Ό λ§žμΆ€ν˜•μœΌλ‘œ λŒ€μ‘ν•˜λŠ” λ™μ‹œμ— μ •λŸ‰μ μ΄κ³  μ‹€μ²œμ μΈ ν•΄κ²°λ°©μ•ˆμ„ λ§ˆλ ¨ν•˜κΈ° μœ„ν•΄μ„œ μ‹œμŠ€ν…œ κ΄€μ μ—μ„œ ν•΄λ‹Ή ν˜„μƒμ˜ ꡬ체성을 νŒŒμ•…ν•  ν•„μš”κ°€ μžˆλ‹€. 이에 λ³Έ μ—°κ΅¬λŠ” λ†μ΄Œμ§€μ—­μ— λŒ€ν•œ μƒνƒœ-μ‚¬νšŒ μ‹œμŠ€ν…œμ˜ ν˜„μ•ˆλ“€μ„ μ‹œμŠ€ν…œ κ΄€μ μ—μ„œ ν•΄κ²°ν•  수 μžˆλŠ” 문제둜 μ •μ˜ν•˜κ³ , λ°μ΄ν„°μ‚¬μ΄μ–ΈμŠ€ 기법을 μ΄μš©ν•˜μ—¬ μ‹œμŠ€ν…œ μ ‘κ·Όλ°©λ²•μœΌλ‘œ 해법을 찾을 수 μžˆλŠ” λ°©μ•ˆμ„ λͺ¨μƒ‰ν•˜κ³ μž ν•˜μ˜€λ‹€. 이λ₯Ό μœ„ν•΄ λ¨Όμ € (1) μ§€μ—­κ°œλ°œμ‚¬μ—…κ³Ό κ΄€λ ¨λœ λ¬Έν—Œ κ²€ν† λ₯Ό μˆ˜ν–‰ν•˜μ˜€μœΌλ©°, λ†μ΄Œμ§€μ—­μ˜ 문제λ₯Ό μ •μ£Όν™˜κ²½κ°œμ„ κ³Ό μ†Œλ“ν–₯μƒμ˜ 핡심뢄야인 ꡐ윑, 의료, μœ ν†΅κ°œμ„ , λΆ€κ°€κ°€μΉ˜ 창좜과 κ΄€λ ¨ν•œ 주제의 ν˜„μ•ˆμœΌλ‘œ μ •ν˜•ν™”ν•˜μ˜€λ‹€. (2) 각각의 ν˜„μ•ˆλ“€μ— λŒ€ν•˜μ—¬ μ‹œμŠ€ν…œ κ΄€μ μ—μ„œ 문제λ₯Ό μ •μ˜ν•˜κ³ , λ°μ΄ν„°μ‚¬μ΄μ–ΈμŠ€ 기반의 뢄석기법을 λ°”νƒ•μœΌλ‘œ 문제λ₯Ό ν•΄κ²°ν•˜λŠ” 일련의 과정을 μˆ˜ν–‰ν•˜μ˜€λ‹€. (3) μ΄λŸ¬ν•œ 뢄석과정을 톡해 λ†μ΄Œμ§€μ—­ μ‹œμŠ€ν…œμ„ κ΅¬μ„±ν•˜λŠ” λ‹€μ–‘ν•œ μš”μ†Œλ“€μ˜ 데이터에 λŒ€ν•œ ν™œμš©κ°€λŠ₯μ„±κ³Ό μ μ ˆν•œ 뢄석기법에 λŒ€ν•œ μ μš©μ„±μ„ ν‰κ°€ν•˜μ˜€λ‹€. β€˜μ§€μ—­λ¬Έμ œ λ„μΆœ 및 μœ ν˜•ν™” λ°©μ•ˆ μ—°κ΅¬β€™μ—μ„œλŠ” 정뢀별 κ΅­μ •μš΄μ˜ 5κ°œλ…„ κ³„νšμ— μ œμ‹œλœ κ΅­κ°€ 비전이 μ§€μ—­κ°œλ°œμ‚¬μ—…κ³Ό κ΄€λ ¨ν•œ κ΅­μ •λͺ©ν‘œ 및 κ΅­μ •μ „λž΅, κ΅­μ •κ³Όμ œμ— μ–΄λ– ν•œ 영ν–₯을 λ―ΈμΉ˜λŠ”μ§€ κ³ μ°°ν•˜μ˜€λ‹€. μ§€μ—­κ°œλ°œμ‚¬μ—…κ³Ό κ΄€λ ¨ν•œ λ¬Έν—Œ κ²€ν† λ₯Ό 톡해 μ§€μ—­λ¬Έμ œλŠ” 크게 정주와 μ†Œλ“μœΌλ‘œ λ„μΆœν•  수 있으며, ꡬ체적으둜 μƒν™œν™˜κ²½μ •λΉ„λ₯Ό ν†΅ν•œ μ •μ£Όν™˜κ²½ κ°œμ„ κ³Ό κ²½μ œν™œλ™ 닀각화λ₯Ό ν†΅ν•œ μ†Œλ“ν–₯상 λ°©μ•ˆμ„ λͺ¨μƒ‰ν•˜λŠ” 두 κ°€μ§€λ‘œ μœ ν˜•ν™”ν•˜μ˜€λ‹€. β€˜λ†μ΄Œ μ •μ£Όν™˜κ²½ κ°œμ„ μ„ μœ„ν•œ μ‹œμŠ€ν…œ 뢄석 μ—°κ΅¬β€™μ—μ„œλŠ” 크게 지역이 λ‹Ήλ©΄ν•œ ν˜„μ•ˆ 쀑 κ΅μœ‘λΆ„μ•Όμ™€ μ‘κΈ‰μ˜λ£ŒλΆ„μ•Όμ˜ 문제λ₯Ό μ •μ˜ν•˜κ³  이λ₯Ό ν•΄κ²°ν•˜λŠ” 연ꡬλ₯Ό μˆ˜ν–‰ν•˜μ˜€λ‹€. κ΅μœ‘λΆ„μ•Όμ˜ 경우 학령인ꡬ κ°μ†Œμ— λ”°λ₯Έ λ†μ΄Œμ§€μ—­μ˜ κ΅μœ‘μ‹œμ„€ 톡폐합을 μœ„ν•΄ νœ΄λ¦¬μŠ€ν‹± κ³΅κ°„μ΅œμ ν™” 기법을 μ΄μš©ν•˜μ—¬ ν•™κ΅μ˜ 운영 ν˜Ήμ€ 폐ꡐ에 λŒ€ν•œ μ˜μ‚¬κ²°μ •μ„ 내릴 수 μžˆλŠ” λ°©μ•ˆμ„ λͺ¨μƒ‰ν•˜μ˜€λ‹€. μ‘κΈ‰μ˜λ£ŒλΆ„μ•Όμ˜ 경우 λ„μ‹œμ™€ λ†μ΄Œμ§€μ—­μ˜ μ‹œκ°„λŒ€λ³„ μ‹€μ‹œκ°„ λ„λ‘œμ†λ„ 변화에 λ”°λ₯Έ μ‘κΈ‰μ˜λ£Œ μ ‘κ·Όμ„± λ³€ν™”λ₯Ό λΆ„μ„ν•˜κ³  이에 λ”°λ₯Έ μ‘κΈ‰μ˜λ£Œ 취약지와 μ‘κΈ‰ν™˜μž μƒμ‘΄μœ¨μ„ ν‰κ°€ν•˜λ©°, λ‹€μ–‘ν•œ 응급상황 μ‹œλ‚˜λ¦¬μ˜€λ₯Ό κ΅¬μΆ•ν•˜μ—¬ 상황별 생쑴확λ₯  λ³€ν™” 뢄석을 톡해 κ°œμ„ λ°©μ•ˆμ„ λ„μΆœν•˜μ˜€λ‹€. β€˜λ†μ΄Œ μ†Œλ“ν–₯상을 μœ„ν•œ μ‹œμŠ€ν…œ 뢄석 μ—°κ΅¬β€™μ—μ„œλŠ” μœ ν†΅κ°œμ„  및 λΆ€κ°€κ°€μΉ˜ 창좜 λΆ„μ•Όμ˜ 문제λ₯Ό μ •μ˜ν•˜κ³  이λ₯Ό ν•΄κ²°ν•˜λŠ” 연ꡬλ₯Ό μˆ˜ν–‰ν•˜μ˜€λ‹€. μœ ν†΅κ°œμ„ μ˜ 경우 농산물 μš΄μ†‘μ˜ ν•œκ³„λΉ„μš©μ„ μ΅œμ†Œν™”ν•˜κΈ° μœ„ν•˜μ—¬ κ΄‘μ—­κ΅ν†΅λ§μ˜ μœ νœ΄κ³΅κ°„κ³Ό μΉœν™˜κ²½ μš΄μ†‘μˆ˜λ‹¨μ„ μ΄μš©ν•œ μƒˆλ‘œμš΄ ν˜•νƒœμ˜ μŠ€λ§ˆνŠΈλ‘œμ§€μŠ€ν‹±μŠ€ μ‹œμŠ€ν…œμ„ κ°œλ°œν•˜κ³ , 기쑴의 택배망과 비ꡐλ₯Ό 톡해 μ μš©κ°€λŠ₯성을 ν‰κ°€ν•˜μ˜€λ‹€. λΆ€κ°€κ°€μΉ˜ 창좜 λΆ„μ•Όμ—μ„œλŠ” μ €νƒ„μ†Œλ†μ‚°λ¬ΌμΈμ¦μ œλ„λ₯Ό λŒ€μƒμœΌλ‘œ 톡계적 μΆ”λ‘ κΈ°λ°˜μ˜ 인증기쀀 μ„€μ • λ°©μ•ˆμ„ λͺ¨μƒ‰ν•˜μ˜€λ‹€. κΈ°μ‘΄ 인증기쀀인 ꡭ가평균값과 농업 μƒμ‚°ν™˜κ²½μ˜ λΆˆν™•μ‹€μ„±μ„ κ³ λ €ν•œ 톡계적 μΆ”λ‘ κ°’κ³Ό 비ꡐλ₯Ό 톡해 μ €νƒ„μ†Œλ†μ‚°λ¬ΌμΈμ¦μ œλ„μ˜ ν†΅κ³„μ μœΌλ‘œ μœ μ˜ν•œ μˆ˜μ€€μ—μ„œμ˜ 인증기쀀에 λŒ€ν•œ 톡계적 λŒ€μ•ˆμ„ μ œμ‹œν•˜μ˜€λ‹€. μ§€μ—­κ°œλ°œ 및 κ³΅κ°„κ³„νš 뢄야에 κΈ°μ—¬ν•  수 μžˆλŠ” λ³Έ μ—°κ΅¬μ˜ ν•™μˆ μ  μ€‘μš”μ„±μ€ λ‹€μŒκ³Ό κ°™λ‹€. λ¨Όμ € 지리정보와 ν†΅κ³„μ •λ³΄λΏλ§Œ μ•„λ‹ˆλΌ μ‹€μ‹œκ°„ ꡐ톡정보 λ“± λ‹€μ–‘ν•œ ν˜•νƒœμ˜ 빅데이터λ₯Ό 기반으둜 λ†μ΄Œμ§€μ—­μ΄ 가진 νŠΉμ„±λ“€μ„ κ³ λ €ν•˜μ—¬ 문제λ₯Ό ν•΄κ²°ν•  수 μžˆλŠ” λ°μ΄ν„°μ‚¬μ΄μ–ΈμŠ€ 기반의 μ •λŸ‰μ μΈ λ°©μ•ˆμ„ μ œμ‹œν•˜μ˜€λ‹€. λ˜ν•œ μ‹œμŠ€ν…œ κ΄€μ μ—μ„œ μ§€μ—­μ˜ 문제λ₯Ό μ •ν˜•ν™”ν•˜μ—¬ ν•΄κ²°ν•  수 μžˆλŠ” μ •λŸ‰μ μΈ 뢄석기법에 λŒ€ν•œ 사둀λ₯Ό 톡해 μ‹€μ²œμ μΈ λ°©μ•ˆμ„ λͺ¨μƒ‰ν•  수 μžˆλ„λ‘ λ°©ν–₯을 μ œμ‹œν•˜μ˜€λ‹€. 이λ₯Ό 톡해 λ³Έ μ—°κ΅¬λŠ” 기쑴의 행정ꡬ역 λ‹¨μœ„μ˜ ν†΅κ³„μžλ£Œλ₯Ό 기반으둜 ν•œ μ •μ±… 수립과 같은 ν”„λ‘œμ„ΈμŠ€λ₯Ό νƒˆν”Όν•˜κ³ , 보닀 μ •λŸ‰μ μΈ 방법둠을 톡해 데이터λ₯Ό 기반으둜 ν•œ 정책을 μˆ˜λ¦½ν•  수 μžˆλŠ” 기초λ₯Ό λ§ˆλ ¨ν•  수 μžˆλ‹€κ³  νŒλ‹¨λœλ‹€. μ΄λŠ” ν–₯ν›„ λ†μ΄Œμ§€μ—­μ˜ 보건·볡지, ꡐ윑, μ‚°μ—… λ“± λ‹€μ–‘ν•œ 뢄야에 μˆ˜μš”λ§žμΆ€ν˜• 증거기반 정책에 λŒ€ν•œ μ˜μ‚¬κ²°μ •μ„ 지원할 수 있으며, κ΄€λ ¨λœ λ²•Β·μ œλ„ κ°œνŽΈμ— 합리적이고 μ •λŸ‰μ μΈ κ·Όκ±°λ₯Ό λ§ˆλ ¨ν•˜κ³  기초자료둜써 μ œκ³΅ν•  수 μžˆλ‹€κ³  μ‚¬λ£Œλœλ‹€.The development of big data and knowledge information technology enables researchers to find effective ways to use data as evidence for making decisions and policies and solving problems. Data sciences also help scholars accurately recognize problems with systems, identify key data to solve problems, and analyze data using appropriate techniques to produce meaningful results. In agricultural and rural regions, governments also seek derive quantitative approaches to solve problems by considering regional characteristics while effectively utilizing limited resources in poor environments such as a diminishing population, aging, and hollowing in rural areas. Thus, it is necessary to identify the specifics issues related to the phenomenon based on system perspectives using data science and to identify quantitative, customized, and practical solutions ongoing issues in rural areas. The main objective of this dissertation is to define the ecological-social systems issues in rural areas. These problems can be solved from system perspectives, and solutions can be found based on data science techniques. First, this dissertation reviewed the literature related to regional development projects in South Korea and categorized rural issues such as improving the settlement conditions and creating income sources. Second, for each issue, the problem was defined from a system perspectives and processes to solve the problem were recommended based on data science-based analytical techniques. Third, through this analysis process, the study evaluated the availability of data from various components of rural systems and their applicability to appropriate analytical techniques. In the chapter titled, "A Study on the Derivation and Categorization of Regional Problems," the impact of Korea's national vision, national goals, national strategy, and national tasks were presented in each government's five-year plan related to the composition and implementation of regional development projects. Through the literature review related to regional development projects, the regional issues were categorized into two types: (1) settlement environment improvement by maintaining the living environment and (2) income creation by diversifying economic activities. The chapter titled, "System Analysis for the Improvement of Rural Settlement Environment," two issues were addressed to define and solve problems in the education and emergency medical sectors. The first study in the education field analyzed and recommended solutions on the operation or closure of schools using heuristic spatial optimization techniques to consolidate educational facilities in rural areas due to the decreasing school-age population. The second study in the emergency medical field analyzed changes in accessibility to emergency medical services due to real-time road speed changes in urban and rural areas. Emergency medical vulnerabilities and survival rate of emergency patients were also analyzed, and various emergency scenarios were constructed to recommend improvement measures based on the survival probability change analysis. The chapter on "System Analysis for Rural Income Creation," analyzed problems related to improving crop distribution and value-added generation. In the distribution improvement study, a new type of smart logistic system was suggested using idle space and eco-friendly transportation in a regional network to minimize the marginal cost of agricultural transportation. Applicability was also evaluated by comparing the existing delivery networks. The study in the value-added generation field aimed to establish statistical inference-based certification standards for low-carbon agricultural product certification systems. Statistical alternatives to appropriate certification criteria for low-carbon agricultural production certification schemes were also proposed by comparing the existing national average values considering the uncertainties in agricultural production conditions. This dissertation with a series of studies contributes to regional development and planning and provide the following academic significance. First, this dissertation presents data science-based quantitative measures to solve problems considering rural characteristics by applying various types of big data such as real-time traffic information as well as geographical and statistical information. In addition, a direction to explore practical measures is presented using examples of quantitative analytical techniques that can be structured and solved by formalizing regional problems from a systems perspective. This dissertation also addresses the limitations of existing studies on rural policies based on administrative statistics and lays the groundwork for establishing data-based policies using more quantitative methodologies. The results can support evidence-based policy decisions tailored to the demands in various fields including health, welfare, education, and industry in rural areas in the future. The recommendations also provide reasonable and quantitative grounds for reforming related laws, policies, and regulations.제 1 μž₯ μ„œ λ‘  1 제 1 절 연ꡬ λ°°κ²½ 및 λͺ©μ  3 1. μ—°κ΅¬μ˜ λ°°κ²½ 3 2. μ—°κ΅¬μ˜ λͺ©μ  8 제 2 절 연ꡬ ꡬ성 9 제 2 μž₯ κΈ°λ³Έ 이둠 13 제 1 절 λ°μ΄ν„°μ‚¬μ΄μ–ΈμŠ€ 15 제 2 절 λ°μ΄ν„°μ‚¬μ΄μ–ΈμŠ€ 기반의 μ§€μ—­λ¬Έμ œ 해결을 μœ„ν•œ 방법둠 19 1. μ ‘κ·Όμ„± 평가λ₯Ό μœ„ν•œ λ„€νŠΈμ›Œν¬ 뢄석 19 2. μ‹œμ„€μž…μ§€μ„€μ •μ„ μœ„ν•œ κ³΅κ°„μ΅œμ ν™” 기법 22 3. ν™˜κ²½μ˜ν–₯ 평가λ₯Ό μœ„ν•œ 전과정평가 기법 26 4. μ •λŸ‰μ  κΈ°μ€€ λ§ˆλ ¨μ„ μœ„ν•œ 톡계적 μΆ”λ‘  방법 32 제 3 μž₯ μ§€μ—­λ¬Έμ œ λ„μΆœ 및 μœ ν˜•ν™” λ°©μ•ˆ 연ꡬ 35 제 1 절 정뢀별 μ§€μ—­κ°œλ°œμ‚¬μ—… μ •μ±… λ³€ν™” 뢄석 37 1. μ„œλ‘  37 1.1. λ°°κ²½ 및 ν•„μš”μ„± 37 1.2. 연ꡬλͺ©μ  39 2. 연ꡬ 자료 및 방법 40 2.1. μ§€μ—­κ°œλ°œμ‚¬μ—… κ΄€λ ¨μžλ£Œ 40 3. 뢄석 κ²°κ³Ό 41 3.1. μ§€μ—­κ°œλ°œμ‚¬μ—… 정책에 λŒ€ν•œ 정뢀별 좔진과정 41 3.1.1. 정뢀별 κ΅­μ •μš΄μ˜ κ³„νš 41 3.1.2. 정뢀별 κ΅­κ°€κ· ν˜•λ°œμ „ κΈ°λ³Έκ³„νš 44 3.1.3. 정뢀별 농어업인 μ‚Άμ˜ 질 ν–₯상 및 λ†μ‚°μ–΄μ΄Œ μ§€μ—­κ°œλ°œ κΈ°λ³Έκ³„νš 49 3.2. 정뢀별 μ§€μ—­κ°œλ°œμ‚¬μ—…μ˜ νŠΉμ§• 및 μ„±κ³Ό 54 3.2.1. 정뢀별 μ§€μ—­κ°œλ°œμ‚¬μ—… ꡬ성 및 νŠΉμ§• 54 3.2.2. 정뢀별 μ§€μ—­κ°œλ°œμ‚¬μ—… μ„±κ³Ό 및 쒅합평가 58 4. κ³ μ°° 64 5. μ†Œκ²° 65 제 4 μž₯ 지역 μ •μ£Όν™˜κ²½ κ°œμ„ μ„ μœ„ν•œ μ‹œμŠ€ν…œ 뢄석 연ꡬ 67 제 1 절 학령인ꡬ κ°μ†Œμ— λ”°λ₯Έ 톡학접근성 λ³€ν™”λ₯Ό κ³ λ €ν•œ κ΅μœ‘μ‹œμ„€μ˜ μž…μ§€μ΅œμ ν™” λͺ¨λΈ 개발 69 1. μ„œλ‘  69 1.1. λ°°κ²½ 및 ν•„μš”μ„± 69 1.2. 연ꡬλͺ©μ  73 2. 뢄석 방법 및 자료 74 2.1. μ΄ˆλ“±κ΅μœ‘μ‹œμ„€ 및 학ꡬ도 데이터 74 2.1.1. 지역별 μ΄ˆλ“±κ΅μœ‘μ‹œμ„€ 데이터 74 2.1.2. 학ꡐ별 학ꡬ도 데이터 77 2.2. 지역별 λ§ˆμ„λ‹¨μœ„ μƒν™œκΆŒ 쀑심지 μ„€μ • 78 2.3. μ‹€μ œλ„λ‘œκ±°λ¦¬ 기반의 톡학접근성 뢄석 81 2.3.1. λ„λ‘œλ§λ„λ₯Ό μ΄μš©ν•œ μ‹€μ œ λ„λ‘œκ±°λ¦¬ μ‚°μ • 81 2.3.2. κ΅μœ‘μ‹œμ„€ μ ‘κ·Όμ„± μ§€ν‘œλ₯Ό μ΄μš©ν•œ 톡학접근성 평가 83 2.4. κ΅μœ‘ν˜•ν‰μ„± 기반의 졜적 ν•™κ΅° μž¬μ„€μ • μž…μ§€μ΅œμ ν™” λͺ¨λΈ 개발 85 2.4.1. ν•˜μ΄λΈŒλ¦¬λ“œ νœ΄λ¦¬μŠ€ν‹± p-median 문제 μ•Œκ³ λ¦¬μ¦˜ 85 2.4.2. p-median μ•Œκ³ λ¦¬μ¦˜μ˜ νœ΄λ¦¬μŠ€ν‹± μˆœμ„œλ„ 88 3. 뢄석 κ²°κ³Ό 91 3.1. μ΄ˆλ“±κ΅μœ‘μ‹œμ„€μ˜ 도농간 톡학접근성 λ³€ν™” 91 3.1.1. μ‹ μ„€ 및 톡폐합에 λ”°λ₯Έ μ‹œκ³„μ—΄μ  톡학접근성 λ³€ν™” 91 3.1.2. 학ꡬ지정에 λ”°λ₯Έ λ§ˆμ„λ‹¨μœ„ 톡학접근성 λ³€ν™” 97 3.2. 학령인ꡬ κ°μ†Œλ₯Ό κ³ λ €ν•œ νœ΄λ¦¬μŠ€ν‹± κ³΅κ°„μ΅œμ ν™” 기반의 κ΅μœ‘μ‹œμ„€ μž…μ§€ λͺ¨λΈ 개발 100 3.2.1. 사둀 연ꡬ지역 100 3.2.2. 기쑴의 ν•™κ΅°κ³Ό λͺ¨μ˜λœ 졜적 ν•™κ΅° 비ꡐ 102 3.2.3. μ‹€μ œ 폐ꡐ μˆœμœ„μ™€ μ‹œλ‚˜λ¦¬μ˜€μ— λ”°λ₯Έ 폐ꡐ μˆœμœ„ 비ꡐ 104 4. κ³ μ°° 111 5. μ†Œκ²° 113 제 2 절 μ‹€μ‹œκ°„ ꡐ톡정보 기반의 μ‘κΈ‰μ˜λ£Œ 취약지 및 생쑴λ₯  뢄석 115 1. μ„œλ‘  115 1.1. λ°°κ²½ 및 ν•„μš”μ„± 115 1.2. 연ꡬλͺ©μ  118 2. 뢄석 방법 및 자료 119 2.1. μ‘κΈ‰μ˜λ£Œμ‹œμ„€ 및 μ‹€μ‹œκ°„ ꡐ톡 속도 정보 μˆ˜μ§‘ 119 2.2. μ‹œμ„€ μœ„μΉ˜μ •λ³΄ λ³€ν™˜ 및 μ •μ œ 122 2.3. 속성정보 μœ΅ν•©ν•œ ꡐ톡흐름 λ„λ‘œλ§ ꡬ좕 124 2.4. μ‹€μ‹œκ°„ μ‘κΈ‰μ˜λ£Œμ„œλΉ„μŠ€ μ ‘κ·Ό λ„€νŠΈμ›Œν¬ λͺ¨λΈ 127 2.2. μ‘κΈ‰μ˜λ£Œ 취약지 및 응급상황별 생쑴λ₯  129 2.2.1. μ‘κΈ‰μ˜λ£Œ 취약지 μ„ μ • κΈ°μ€€ 129 2.2.2. 응급상황 μ •μ˜ 131 2.2.3. 응급상황별 생쑴λ₯  133 3. 뢄석 κ²°κ³Ό 134 3.1. 도농간 μ˜λ£Œν™˜κ²½ 및 λ„λ‘œμ΄μš©μƒν™© 비ꡐ 134 3.1.1. 도농간 μ˜λ£Œν™˜κ²½ 비ꡐ 134 3.1.2. 도농간 μ‹œκ°„λŒ€λ³„ λ„λ‘œμ΄μš©μƒν™© 비ꡐ 137 3.2. λ„λ‘œμ†λ„μ— λ”°λ₯Έ μ‘κΈ‰μ˜λ£Œμ‹œμ„€μ˜ μ„œλΉ„μŠ€ κΆŒμ—­ 및 취약인ꡬ λ²”μœ„ 139 3.2.1. μ œν•œμ†λ„μ™€ μ‹€μ‹œκ°„ ꡐ톡흐름 속도에 λ”°λ₯Έ μ„œλΉ„μŠ€ κΆŒμ—­ λ²”μœ„ 139 3.2.2. μ œν•œμ†λ„μ™€ μ‹€μ‹œκ°„ ꡐ톡흐름 속도에 λ”°λ₯Έ μ„œλΉ„μŠ€ μ·¨μ•½ 인ꡬ 145 3.3. λ§ˆμ„λ‹¨μœ„ μ‹€μ‹œκ°„ ꡐ톡정보에 λ”°λ₯Έ μ˜λ£Œμ·¨μ•½μ§€ μž¬ν‰κ°€ 146 3.4. 지역별 μ‘κΈ‰μ˜λ£Œν™˜μžμ˜ μ‹œκ°„λŒ€λ³„ 생쑴λ₯  뢄석 148 3.3.1. 도농간 μ‹œκ°„λŒ€λ³„ 생쑴λ₯  λ³€ν™” 148 3.3.2. 응급상황별 생쑴λ₯  λ³€ν™” 152 4. κ³ μ°° 155 5. μ†Œκ²° 156 제 5 μž₯ 지역 μ†Œλ“ν–₯상을 μœ„ν•œ μ‹œμŠ€ν…œ 뢄석 연ꡬ 159 제 1 절 유휴 μš΄μ†‘μžμ›μ„ ν™œμš©ν•œ 농산물 슀마트 λ‘œμ§€μŠ€ν‹±μŠ€ μ‹œμŠ€ν…œ μ„±λŠ₯ 뢄석 161 1. μ„œλ‘  161 1.1. λ°°κ²½ 및 ν•„μš”μ„± 161 1.2. 연ꡬλͺ©μ  164 2. 뢄석 방법 및 자료 165 2.1. AgroSLS μ‹œμŠ€ν…œ ꡬ쑰 섀계 165 2.2. AgroSLS의 영ν–₯ 평가 ν”„λ ˆμž„μ›Œν¬ 167 2.3. AgroSLS의 κ²½λ‘œλΆ„μ„ 170 2.3.1. λ„λ‘œ λ„€νŠΈμ›Œν¬λ₯Ό ν†΅ν•œ κ²½λ‘œλΆ„μ„ 170 2.3.2. μ§€ν˜•μ •λ³΄λ₯Ό μ΄μš©ν•œ λ“œλ‘  경둜 뢄석 172 2.4. μš΄μ†‘μˆ˜λ‹¨λ³„ μ—λ„ˆμ§€ μ‚¬μš©λŸ‰ μΆ”μ • 174 2.4.1. 트럭 μš΄μ†‘μ˜ μ—λ„ˆμ§€ μ‚¬μš©λŸ‰ 174 2.4.2. λ²„μŠ€ μš΄μ†‘μ˜ μ—λ„ˆμ§€ μ‚¬μš©λŸ‰ 175 2.4.2. λ“œλ‘  μš΄μ†‘μ˜ μ—λ„ˆμ§€ μ‚¬μš©λŸ‰ 176 3. 뢄석 κ²°κ³Ό 179 3.1. λŒ€μƒμ§€μ—­ μ„€μ • 179 3.2. μˆ˜μš”-곡급 가정쑰건 181 3.3. 기쑴의 직거래 μš΄μ†‘λ§κ³Ό AgroSLS의 μš΄μ†‘λ²”μœ„ μΆ”μ • 183 3.3.1. 우체ꡭ 택배망을 μ΄μš©ν•œ 지역배솑 λ²”μœ„ 183 3.3.2. AgroSLSλ₯Ό μ΄μš©ν•œ 지역배솑 λ²”μœ„ 185 3.4. 기쑴의 직거래 μš΄μ†‘λ§κ³Ό AgroSLS의 μ†Œμš”μ‹œκ°„ μΆ”μ • 186 3.4.1. 우체ꡭ 택배망을 μ΄μš©ν•œ μ†Œμš”μ‹œκ°„ 186 3.4.2. AgroSLSλ₯Ό μ΄μš©ν•œ μ†Œμš”μ‹œκ°„ 191 3.4.3. 우체ꡭ 택배망과 AgroSLS의 총 μ†Œμš”μ‹œκ°„ 비ꡐ 194 3.5. 기쑴의 직거래 μš΄μ†‘λ§κ³Ό AgroSLS의 μ—λ„ˆμ§€ μ‚¬μš©λŸ‰ μΆ”μ • 196 3.5.1. 우체ꡭ 택배망을 μ΄μš©ν•œ μ—λ„ˆμ§€ μ‚¬μš©λŸ‰ 196 3.5.2. AgroSLSλ₯Ό μ΄μš©ν•œ μ—λ„ˆμ§€ μ‚¬μš©λŸ‰ 201 3.5.3. 우체ꡭ 택배망과 AgroSLS의 총 μ—λ„ˆμ§€ μ‚¬μš©λŸ‰ 비ꡐ 204 4. κ³ μ°° 205 5. μ†Œκ²° 207 제 2 절 농업 μƒμ‚°μ‹œμŠ€ν…œμ˜ λΆˆν™•μ‹€μ„±μ„ κ³ λ €ν•œ 톡계적 μΆ”λ‘  기반의 μ €νƒ„μ†Œλ†μ‚°λ¬Ό 인증기쀀 평가 209 1. μ„œλ‘  209 1.1. λ°°κ²½ 및 ν•„μš”μ„± 209 1.2. 연ꡬλͺ©μ  213 2. 뢄석 방법 및 자료 214 2.1. 농가 μ˜λ†ν™œλ™ 데이터 214 2.2. 농산물 생산단계 μ˜¨μ‹€κ°€μŠ€ 산정방법 214 2.3. 톡계적 인증기쀀 평가 방법 220 2.3.1. μ ˆμ‚­ν‰κ· λ²• 220 2.3.2. 톡계적 좔정방법 221 3. 뢄석 κ²°κ³Ό 224 3.1. 농산물 μ˜λ†ν™œλ™ 데이터 κΈ°μˆ ν†΅κ³„ 뢄석 224 3.2. 농산물 μž¬λ°°λ‹¨κ³„λ³„ μ˜¨μ‹€κ°€μŠ€ μΆ”μ • 227 3.3. 톡계적 비ꡐλ₯Ό ν†΅ν•œ 인증기쀀 μ„€μ • 230 4. κ³ μ°° 235 5. μ†Œκ²° 238 제 6 μž₯ μ’…ν•© κ²°λ‘  241 μ°Έκ³ λ¬Έν—Œ 249 Abstract 295λ°•
    corecore