[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"$apiParty6fBuHLCPZ1LTYs42XHdVbjpSDOYYPYzyxeAGwSN5Tp8":3,"$apiPartyirufbgSFDoyuUsYf9sqswhLu80RTVza1IREAh7SHrg4":563,"$apiPartyirufbgSFDoyuUsYf9sqswhLu80RTVza1IREAh7SHrg4$H93EERW16b":563},{"product_data":4,"scene_data":21,"task_data":407,"modality_data":441,"domain_data":478},[5,9,12,15,18],{"name":6,"value":7,"add_value":8,"describe":8},"Rivo","1","",{"name":10,"value":11,"add_value":8,"describe":8},"Cubo","2",{"name":13,"value":14,"add_value":8,"describe":8},"Moye","3",{"name":16,"value":17,"add_value":8,"describe":8},"Juro","4",{"name":19,"value":20,"add_value":8,"describe":8},"Ordo","5",[22,73,135,197,232,267,302,337,372],{"name":23,"value":7,"add_value":24,"describe":25,"children":26},"Home & Indoor","sofa","AI enhances everyday home life. Our datasets cover real indoor scenes to support smart devices, robotics, and home intelligence.",[27,29,31,33,35,37,40,43,46,49,52,55,58,61,64,67,70],{"name":28,"value":7},"Living Room",{"name":30,"value":11},"Bedroom",{"name":32,"value":14},"Kitchen",{"name":34,"value":17},"Dining Area",{"name":36,"value":20},"Bathroom",{"name":38,"value":39},"Entrance \u002F Foyer","6",{"name":41,"value":42},"Corridor \u002F Hallway","7",{"name":44,"value":45},"Staircase","8",{"name":47,"value":48},"Home Office","9",{"name":50,"value":51},"Hobby \u002F Game Room","10",{"name":53,"value":54},"Worship Space","11",{"name":56,"value":57},"Garage","12",{"name":59,"value":60},"Utility \u002F Laundry Room","13",{"name":62,"value":63},"Pantry","14",{"name":65,"value":66},"Basement","15",{"name":68,"value":69},"Garden","16",{"name":71,"value":72},"Balcony","17",{"name":74,"value":11,"add_value":75,"describe":76,"children":77},"Office & Educational","workshop","AI is reshaping work and learning. Our datasets capture offices and classrooms to power automation and next-generation productivity tools.",[78,81,84,87,90,93,96,99,102,105,108,111,114,117,120,123,126,129,132],{"name":79,"value":80},"Open Office","18",{"name":82,"value":83},"Private Office","19",{"name":85,"value":86},"Co-working Space","20",{"name":88,"value":89},"Reception \u002F Lobby","21",{"name":91,"value":92},"Conference Room","22",{"name":94,"value":95},"Huddle Room \u002F Booth","23",{"name":97,"value":98},"Lecture Hall \u002F Auditorium","24",{"name":100,"value":101},"Classroom","25",{"name":103,"value":104},"Science Laboratory","26",{"name":106,"value":107},"Library","27",{"name":109,"value":110},"Design Studio","28",{"name":112,"value":113},"Pantry \u002F Breakroom","29",{"name":115,"value":116},"Cafeteria \u002F Canteen","30",{"name":118,"value":119},"Restroom (Commercial)","31",{"name":121,"value":122},"Gymnasium \u002F Sports Hall","32",{"name":124,"value":125},"Server Room","33",{"name":127,"value":128},"Mailroom \u002F Logistics","34",{"name":130,"value":131},"Janitorial Closet","35",{"name":133,"value":134},"Corridor \u002F Elevators","36",{"name":136,"value":14,"add_value":137,"describe":138,"children":139},"Healthcare & Medical","love-and-help","AI is advancing modern healthcare. Our datasets include clinics and hospitals to enable clinical insights and medical automation.",[140,143,146,149,152,155,158,161,164,167,170,173,176,179,182,185,188,191,194],{"name":141,"value":142},"Operating Theatre \u002F OR","37",{"name":144,"value":145},"Consultation Room","38",{"name":147,"value":148},"Treatment Room","39",{"name":150,"value":151},"Dental Clinic","40",{"name":153,"value":154},"Inpatient Ward","41",{"name":156,"value":157},"Nurse Station","42",{"name":159,"value":160},"ICU","43",{"name":162,"value":163},"NICU (Neonatal ICU)","44",{"name":165,"value":166},"Emergency Room (ER)","45",{"name":168,"value":169},"Hospital Corridor","46",{"name":171,"value":172},"Waiting Area","47",{"name":174,"value":175},"CT\u002FMRI","48",{"name":177,"value":178},"Medical Laboratory","49",{"name":180,"value":181},"Phlebotomy Room","50",{"name":183,"value":184},"Rehabilitation Gym","51",{"name":186,"value":187},"Assisted Living Room","52",{"name":189,"value":190},"Pharmacy","53",{"name":192,"value":193},"Sterile Processing Dept","54",{"name":195,"value":196},"Medical Storage","55",{"name":198,"value":17,"add_value":199,"describe":200,"children":201},"Business & Public Service","business","AI is elevating commercial and public services. Our datasets span retail, dining, and service centers to improve intelligent operations.",[202,205,208,211,214,217,220,223,226,229],{"name":203,"value":204},"Shopping Mall Atrium","86",{"name":206,"value":207},"Supermarket Shelf","87",{"name":209,"value":210},"Self-Checkout Counter","88",{"name":212,"value":213},"Restaurant Dining Hall","89",{"name":215,"value":216},"Commercial Kitchen","90",{"name":218,"value":219},"Hotel Lobby","91",{"name":221,"value":222},"Subway Platform","92",{"name":224,"value":225},"Security Checkpoint","93",{"name":227,"value":228},"Underground Parking","94",{"name":230,"value":231},"Bank Teller Zone","95",{"name":233,"value":20,"add_value":234,"describe":235,"children":236},"Industrial & Manufacturing","robot-arm","AI is modernizing industry. Our datasets capture factories and logistics spaces to support robotics and intelligent manufacturing.",[237,240,243,246,249,252,255,258,261,264],{"name":238,"value":239},"Final Assembly Line","96",{"name":241,"value":242},"Quality Control Station","97",{"name":244,"value":245},"Robotic Welding Cell","98",{"name":247,"value":248},"CNC Machining Center","99",{"name":250,"value":251},"Cleanroom","100",{"name":253,"value":254},"Automated Warehouse","101",{"name":256,"value":257},"Loading Dock","102",{"name":259,"value":260},"Sorting Center","103",{"name":262,"value":263},"Chemical Plant","104",{"name":265,"value":266},"Power Substation","105",{"name":268,"value":39,"add_value":269,"describe":270,"children":271},"Transportation & Driving","car","AI is revolutionizing mobility. Our datasets capture road networks, vehicle dynamics and traffic scenarios to support autonomous driving and intelligent transportation systems.",[272,275,278,281,284,287,290,293,296,299],{"name":273,"value":274},"Urban Intersection","56",{"name":276,"value":277},"Highway \u002F Expressway","57",{"name":279,"value":280},"Tunnel","58",{"name":282,"value":283},"Roundabout","59",{"name":285,"value":286},"School \u002F Hospital Zone","60",{"name":288,"value":289},"Toll Station","61",{"name":291,"value":292},"Construction Zone","62",{"name":294,"value":295},"Parking Garage","63",{"name":297,"value":298},"Driver Cabin","64",{"name":300,"value":301},"Adverse Weather","65",{"name":303,"value":42,"add_value":304,"describe":305,"children":306},"Outdoor & Construction","tent-tree","AI is optimizing outdoor operations. Our datasets capture construction sites, open-air work zones and outdoor infrastructure to support smart construction and autonomous outdoor machinery.",[307,310,313,316,319,322,325,328,331,334],{"name":308,"value":309},"Excavation Site","66",{"name":311,"value":312},"Scaffolding Area","67",{"name":314,"value":315},"Material Storage Yard","68",{"name":317,"value":318},"Site Entrance","69",{"name":320,"value":321},"Roadwork Zone","70",{"name":323,"value":324},"Bridge Infrastructure","71",{"name":326,"value":327},"Transmission Line","72",{"name":329,"value":330},"Open-pit Mine","73",{"name":332,"value":333},"Tunneling Site","74",{"name":335,"value":336},"Post-Disaster Rubble","75",{"name":338,"value":45,"add_value":339,"describe":340,"children":341},"Nature, Aerial & Aquatic","global-loop","AI is exploring the natural world. Our datasets capture terrestrial landscapes, aerial vistas and aquatic ecosystems to support environmental monitoring and autonomous exploration systems.",[342,345,348,351,354,357,360,363,366,369],{"name":343,"value":344},"Deep Forest","76",{"name":346,"value":347},"Farmland \u002F Crops","77",{"name":349,"value":350},"River \u002F Lake","78",{"name":352,"value":353},"Open Ocean","79",{"name":355,"value":356},"Underwater Coral Reef","80",{"name":358,"value":359},"Fish Farm","81",{"name":361,"value":362},"Mountain Terrain","82",{"name":364,"value":365},"Urban Low Altitude","83",{"name":367,"value":368},"Fire Scene","84",{"name":370,"value":371},"Desert \u002F Gobi","85",{"name":373,"value":48,"add_value":374,"describe":375,"children":376},"Virtul & Digital","siri","AI is reshaping the virtual realm. Our datasets capture digital twins, virtual environments and simulated spaces to support metaverse development and intelligent digital interaction.",[377,380,383,386,389,392,395,398,401,404],{"name":378,"value":379},"VR Social Space","106",{"name":381,"value":382},"Synthetic Driving Sim","107",{"name":384,"value":385},"Digital Twin City","108",{"name":387,"value":388},"FPS \u002F MOBA Game","109",{"name":390,"value":391},"Robotics Gym","110",{"name":393,"value":394},"AR Navigation","111",{"name":396,"value":397},"Virtual Showroom","112",{"name":399,"value":400},"Code \u002F IDE Interface","113",{"name":402,"value":403},"App GUI Screen","114",{"name":405,"value":406},"Synthetic 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座舱，通过语音、手势、面部识别等实现人机交互，如语音控制导航、音乐播放。\n驾驶员状态监测：识别疲劳、分心、抽烟、打电话等行为，通过大模型判断危险等级，触发相应提醒或干预机制。\n智能驾驶：AI 用于环境感知、路径规划与决策控制，使车辆能识别道路、行人、障碍物等，实现自适应巡航、自动泊车、车道保持等功能，提升驾驶安全性与便利性。",{"id":492,"value":492,"name":136,"intro":493,"add_value":137,"describe":493},4,"医学影像诊断：分析 CT、MRI 等影像，辅助医生检测疾病、识别病灶，如 AI 系统可快速发现肺部结节。\n医患对话助手：通过自然语言处理理解患者问题，提供初步健康建议或就诊指导，缓解医生接诊压力。\n智能健康管理：根据用户健康数据，提供个性化健康建议、疾病预警，如智能手环结合 AI 分析用户运动、睡眠、心率等数据。",{"id":495,"value":495,"name":496,"intro":497,"add_value":498,"describe":497},6,"Smart Devices","多模态交互：支持语音、手势、眼神等多种交互方式，如 AI 眼镜可通过语音指令实现翻译、搜索功能。\n智能感知与处理：使设备能感知环境、理解用户需求，如智能音箱根据环境噪音自动调节音量。\n个性化服务：根据用户使用习惯和偏好，提供个性化功能与服务，如智能手表为用户定制运动健身计划。","microscope",{"id":500,"value":500,"name":501,"intro":502,"add_value":503,"describe":502},8,"Law & Government","智能法律问答：面向公众或企业用户，提供合规、劳动法、婚姻继承、知识产权等常见法律问题的智能解答。\n合同审查与风险识别：利用大模型分析合同内容，识别潜在风险条款、漏洞或不合理约定，提升合同审核质量。\n法律知识图谱构建：自动梳理法规、案例、条文之间的引用关系，构建语义化知识图谱，支持智能分析和推理。","hammer",{"id":505,"value":505,"name":506,"intro":507,"add_value":508,"describe":507},7,"Education & Training","个性化学习：根据学生学习进度、能力和知识掌握情况，推送个性化学习内容与练习，如智能辅导系统为学生制定专属学习计划。\n智能教学辅助：AI 助教协助教师进行作业批改、答疑解惑，还可分析教学数据，为教师提供教学反馈，优化教学方法。\n虚拟学习环境：利用 AI 创建虚拟实验、历史场景等，让学生沉浸式学习，如在虚拟化学实验室中进行实验操作。","degree-hat",{"id":510,"value":510,"name":511,"intro":512,"add_value":513,"describe":512},5,"Agriculture & Food","作物病虫害识别与防治：通过图像识别分析农作物叶片、果实等症状，识别病虫害类型，给出防治建议，减少产量损失。\n农产品质量检测：利用图像和传感器数据，识别果蔬等农产品的成熟度、外观缺陷，进行自动分级，提高市场竞争力。\n农情监测与预测：利用卫星遥感、气象和传感器数据，结合大模型预测作物长势、干旱、洪涝等农情变化。","ph-farm",{"id":515,"value":515,"name":516,"intro":517,"add_value":518,"describe":517},9,"Retail & E-commerce","智能客服：通过自然语言对话理解用户需求，提供产品推荐、订单查询、退换货支持等服务，提升客户满意度。\n个性化营销推荐：基于用户浏览、购买、偏好等行为数据，生成个性化推荐内容与优惠策略，提高转化率和客单价。\n商品内容生成：自动撰写商品标题、卖点描述、使用说明等内容，适用于海量SKU的内容生产与多语言发布。","buy",{"id":520,"value":520,"name":521,"intro":522,"add_value":523,"describe":8},10,"Security & Protection",null,"safe-shield-line",{"id":525,"value":525,"name":526,"intro":522,"add_value":527,"describe":8},11,"Environment & Climate","weather",{"id":529,"value":529,"name":530,"intro":522,"add_value":531,"describe":8},12,"Energy & Resource","energy-leaf",{"id":533,"value":533,"name":534,"intro":522,"add_value":535,"describe":8},13,"Express & Logistics","speed-outline",{"id":537,"value":537,"name":538,"intro":522,"add_value":539,"describe":8},15,"Sports","baseball-outline",{"id":541,"value":541,"name":542,"intro":522,"add_value":543,"describe":8},16,"General Data","daily-booth",{"id":545,"value":545,"name":546,"intro":522,"add_value":547,"describe":8},17,"Content & Media","media",{"id":549,"value":549,"name":550,"intro":522,"add_value":551,"describe":8},18,"Construction","construction",{"id":553,"value":553,"name":554,"intro":522,"add_value":555,"describe":8},19,"IT & Telecom","tech",{"id":557,"value":557,"name":558,"intro":522,"add_value":498,"describe":8},20,"Science & Research",{"id":560,"value":560,"name":561,"intro":522,"add_value":562,"describe":8},21,"Language & Culture","lang",{"id":564,"unique_code":565,"title":566,"icon":8,"intro":567,"cate":483,"detail":568,"create_time":569,"update_time":570,"price":571,"view_count":572,"download_count":573,"unit":573,"amount":574,"is_create_order":573,"enterprise_id":488,"seo_keywords":575,"seo_description":576,"data_format":577,"file_size":578,"apply_scene":579,"training_task":580,"version":581,"dataset_type_id":492,"dataset_scene_id":529,"sample_file":522,"banner":8,"unit_name":8,"cate_name":449,"icon_url":8,"banner_url":8,"sample_file_url":8,"data_dict":582,"qa_list":613,"sample_metadatas":630,"text_sample_content":660,"enterprise_name":661,"enterprise_logo":662,"data_distribution":663},1078,"b0b86a8b3700ac063cb54d9e4f542df9","Commercial and Industrial Rooftop Solar Feasibility Reasoning Q&A Dataset","Train models to assess commercial and industrial rooftop solar feasibility by reasoning across roof, load, structural, shading, and grid constraints.","\u003Cp>5This dataset organizes text-based project information for commercial and industrial rooftop solar installations, including usable roof area, electricity load profiles, structural limitations, shading, and grid-connection conditions. Its question-and-answer samples cover project context, feasibility questions, verdicts, key constraints, and evidence-based reasoning answers, making the basis for each assessment easier to trace. It is designed for reasoning SFT, training solar project decision analysis, and developing or evaluating models for commercial and industrial distributed solar planning.\u003C\u002Fp>","2026-10-09 18:54:31","2026-10-19 16:30:37","0.00",37,0,5000,"commercial rooftop solar, solar feasibility analysis, solar reasoning Q&A, distributed solar dataset, solar project constraints, reasoning SFT data, solar project assessment","Reasoning Q&A data for commercial rooftop solar, covering roof area, load, structure, shading, and grid constraints for feasibility analysis and SFT.","JSON","0.5GB","rooftop solar feasibility assessment, commercial solar project planning, solar installation evaluation","multi-step reasoning, feasibility assessment, constraint-based reasoning","V1.0",[583,588,593,598,603,608],{"id":573,"name":584,"field":585,"intro":586,"type":587},"File Name","file_name","File name","string",{"id":589,"name":590,"field":591,"intro":592,"type":587},7844,"Question","question","Asks whether a solar project is feasible under the stated conditions or requests an analysis of its limitations.",{"id":594,"name":595,"field":596,"intro":597,"type":587},7845,"Key Constraints","key_constraints","Identifies roof, load, structural, shading, or grid-connection conditions that materially affect project feasibility.",{"id":599,"name":600,"field":601,"intro":602,"type":587},7846,"Project Context and Constraints","project_context","Describes usable roof area, electricity load profile, structural limitations, shading, grid-connection conditions, and other relevant project information.",{"id":604,"name":605,"field":606,"intro":607,"type":587},7847,"Reasoning Answer","reasoning_answer","Provides a final response and a reasoned analysis grounded in the project context and constraints.",{"id":609,"name":610,"field":611,"intro":612,"type":587},7848,"Feasibility Verdict","feasibility_verdict","States the assessment reached after considering the project constraints.",[614,618,622,626],{"id":615,"question":616,"answer":617},5759,"What does the dataset contain?","Samples focus on commercial and industrial rooftop solar projects. They include project context and constraints, feasibility questions, verdicts, key limiting factors, and reasoning answers. Topics may include usable roof area, electricity load, structural conditions, shading, and grid-connection requirements.",{"id":619,"question":620,"answer":621},5760,"Which training and evaluation tasks does it support?","The dataset can support reasoning SFT, project constraint identification, solar feasibility assessment, and decision analysis training. It can also be used to build related evaluation tasks. Data cleaning, splitting, and evaluation criteria should be adapted to the target model and workflow.",{"id":623,"question":624,"answer":625},5761,"How do the fields support reasoning training?","Project conditions, key constraints, feasibility verdicts, and reasoning answers are organized as separate fields. This structure helps models learn to extract constraints from project context, analyze their impact on a proposed system, and provide a supported assessment. Actual reasoning performance depends on the sample content and training setup.",{"id":627,"question":628,"answer":629},5762,"How can I obtain the dataset, and what are the licensing terms?","Use the delivery channel provided on the current dataset listing or platform. Permitted uses, commercial rights, and redistribution restrictions are governed by the specific license terms for this offering. Review those terms and confirm that the data meets your project requirements before use.",[631,642,651],{"id":632,"relate_table":633,"relate_id":634,"file_size":573,"file_name":8,"path":8,"duration":573,"cate":483,"file_format":8,"audio_rate":8,"audio_channel":522,"audio_bit_depth":522,"quality":8,"annotation":635,"cate_name":636,"question":637,"key_constraints":638,"project_context":639,"reasoning_answer":640,"feasibility_verdict":641},14636,"union_cubo",128854047,"{\"question\": \"Is there enough information to determine whether the proposed 300 kWp system is feasible?\", \"key_constraints\": \"The roof's ability to support the proposed system has not been assessed, and the site's permitted inverter capacity and export limit are unconfirmed. The stated daytime demand range alone does not resolve whether the system can operate within the eventual interconnection conditions.\", \"project_context\": \"A metalworking plant is considering a 300 kWp rooftop PV system. The roof has 2,100 m² of area available after access routes and rooftop equipment are excluded, and the proposed layout avoids a section reported to receive afternoon shade. The plant's weekday daytime demand ranges from 240 to 380 kW. No structural capacity assessment or roof load rating has been provided. The utility has not yet confirmed the permitted inverter capacity or export limit for this site. No project-specific interconnection approval has been issued.\", \"reasoning_answer\": \"There is not enough information to determine feasibility. The available roof area and the identified shading exclusion provide some layout context, but no structural assessment or roof load rating is available to establish whether the roof can support the array. The utility's inverter and export limits are also unknown, and no site-specific interconnection approval has been issued. The next decision inputs are a structural assessment for the proposed system and confirmation of the site's allowable interconnection and export conditions. The stated demand range is not sufficient to resolve those missing constraints.\", \"feasibility_verdict\": \"Insufficient information\"}","文本","Is there enough information to determine whether the proposed 300 kWp system is feasible?","The roof's ability to support the proposed system has not been assessed, and the site's permitted inverter capacity and export limit are unconfirmed. The stated daytime demand range alone does not resolve whether the system can operate within the eventual interconnection conditions.","A metalworking plant is considering a 300 kWp rooftop PV system. The roof has 2,100 m² of area available after access routes and rooftop equipment are excluded, and the proposed layout avoids a section reported to receive afternoon shade. The plant's weekday daytime demand ranges from 240 to 380 kW. No structural capacity assessment or roof load rating has been provided. The utility has not yet confirmed the permitted inverter capacity or export limit for this site. No project-specific interconnection approval has been issued.","There is not enough information to determine feasibility. The available roof area and the identified shading exclusion provide some layout context, but no structural assessment or roof load rating is available to establish whether the roof can support the array. The utility's inverter and export limits are also unknown, and no site-specific interconnection approval has been issued. The next decision inputs are a structural assessment for the proposed system and confirmation of the site's allowable interconnection and export conditions. The stated demand range is not sufficient to resolve those missing constraints.","Insufficient information",{"id":643,"relate_table":633,"relate_id":644,"file_size":573,"file_name":8,"path":8,"duration":573,"cate":483,"file_format":8,"audio_rate":8,"audio_channel":522,"audio_bit_depth":522,"quality":8,"annotation":645,"cate_name":636,"question":646,"key_constraints":647,"project_context":648,"reasoning_answer":649,"feasibility_verdict":650},14635,994897134,"{\"question\": \"Can the 200 kWp proposal proceed as currently specified, and what changes or conditions are needed?\", \"key_constraints\": \"The roof needs the identified reinforcement before installation because the proposed array load exceeds the stated existing capacity. The 180 kW AC inverter also requires effective export control to keep exports within the utility's 30 kW limit; the stated minimum daytime demand alone does not establish that exports will always remain within that limit.\", \"project_context\": \"A distribution warehouse has 1,200 m² of roof area available after fire lanes and rooftop equipment are excluded. The initial proposal is a 200 kWp array with a 180 kW AC inverter. A preliminary structural review found that the roof can support an additional load of 0.12 kN\u002Fm², while the proposed array would impose 0.16 kN\u002Fm²; the structural engineer has identified a feasible reinforcement approach, but it has not been completed or approved for construction. The utility has approved a maximum export of 30 kW. The warehouse's recorded daytime demand is at least 120 kW, and the design can use an export-control system. The planned layout avoids the roof section shaded by a neighboring building.\", \"reasoning_answer\": \"The project is conditionally feasible, but the proposal should not proceed unchanged. The proposed array's stated load of 0.16 kN\u002Fm² exceeds the roof's current additional-load capacity of 0.12 kN\u002Fm², so the identified reinforcement must be completed and approved before installation. The utility permits up to 30 kW of export, so the design must include a suitable export-control arrangement and be checked against that limit under operating conditions. The shaded roof section is excluded from the layout, and the remaining area is stated to be available. With the structural work completed and export compliance confirmed, the project can proceed subject to those conditions.\", \"feasibility_verdict\": \"Conditionally feasible\"}","Can the 200 kWp proposal proceed as currently specified, and what changes or conditions are needed?","The roof needs the identified reinforcement before installation because the proposed array load exceeds the stated existing capacity. The 180 kW AC inverter also requires effective export control to keep exports within the utility's 30 kW limit; the stated minimum daytime demand alone does not establish that exports will always remain within that limit.","A distribution warehouse has 1,200 m² of roof area available after fire lanes and rooftop equipment are excluded. The initial proposal is a 200 kWp array with a 180 kW AC inverter. A preliminary structural review found that the roof can support an additional load of 0.12 kN\u002Fm², while the proposed array would impose 0.16 kN\u002Fm²; the structural engineer has identified a feasible reinforcement approach, but it has not been completed or approved for construction. The utility has approved a maximum export of 30 kW. The warehouse's recorded daytime demand is at least 120 kW, and the design can use an export-control system. The planned layout avoids the roof section shaded by a neighboring building.","The project is conditionally feasible, but the proposal should not proceed unchanged. The proposed array's stated load of 0.16 kN\u002Fm² exceeds the roof's current additional-load capacity of 0.12 kN\u002Fm², so the identified reinforcement must be completed and approved before installation. The utility permits up to 30 kW of export, so the design must include a suitable export-control arrangement and be checked against that limit under operating conditions. The shaded roof section is excluded from the layout, and the remaining area is stated to be available. With the structural work completed and export compliance confirmed, the project can proceed subject to those conditions.","Conditionally feasible",{"id":652,"relate_table":633,"relate_id":653,"file_size":573,"file_name":8,"path":8,"duration":573,"cate":483,"file_format":8,"audio_rate":8,"audio_channel":522,"audio_bit_depth":522,"quality":8,"annotation":654,"cate_name":636,"question":655,"key_constraints":656,"project_context":657,"reasoning_answer":658,"feasibility_verdict":659},14634,994784063,"{\"question\": \"Is the proposed rooftop PV system feasible under the stated roof, load, and interconnection conditions?\", \"key_constraints\": \"The design fits within the stated structural capacity and the utility's 300 kW AC interconnection limit. The plant's stated minimum daytime demand of 300 kW exceeds the proposed 250 kW AC inverter capacity, so the stated operating design does not depend on exporting surplus power.\", \"project_context\": \"A food-processing plant has 1,800 m² of roof area available for PV after access paths and equipment clearances. The proposed layout is 270 kWp. The roof engineer has confirmed that the existing structure can support the proposed system without reinforcement. A site survey found no significant shading on the planned array area. The plant's weekday daytime demand is typically 500–720 kW and has not fallen below 300 kW during the past year. The utility has confirmed an interconnection limit of 300 kW AC; the proposed inverter capacity is 250 kW AC, and no export is planned under the operating design.\", \"reasoning_answer\": \"The proposed system is feasible based on the information provided. The roof engineer has confirmed that no structural reinforcement is needed, and the planned array area has no significant shading. The 250 kW AC inverter is below the confirmed 300 kW AC interconnection limit and also below the plant's stated minimum daytime demand of 300 kW. Therefore, the stated conditions do not identify a roof, load, or interconnection constraint that prevents the proposal.\", \"feasibility_verdict\": \"Feasible\"}","Is the proposed rooftop PV system feasible under the stated roof, load, and interconnection conditions?","The design fits within the stated structural capacity and the utility's 300 kW AC interconnection limit. The plant's stated minimum daytime demand of 300 kW exceeds the proposed 250 kW AC inverter capacity, so the stated operating design does not depend on exporting surplus power.","A food-processing plant has 1,800 m² of roof area available for PV after access paths and equipment clearances. The proposed layout is 270 kWp. The roof engineer has confirmed that the existing structure can support the proposed system without reinforcement. A site survey found no significant shading on the planned array area. The plant's weekday daytime demand is typically 500–720 kW and has not fallen below 300 kW during the past year. The utility has confirmed an interconnection limit of 300 kW AC; the proposed inverter capacity is 250 kW AC, and no export is planned under the operating design.","The proposed system is feasible based on the information provided. The roof engineer has confirmed that no structural reinforcement is needed, and the planned array area has no significant shading. The 250 kW AC inverter is below the confirmed 300 kW AC interconnection limit and also below the plant's stated minimum daytime demand of 300 kW. Therefore, the stated conditions do not identify a roof, load, or interconnection constraint that prevents the proposal.","Feasible","{\"question\":\"Is there enough information to determine whether the proposed 300 kWp system is feasible?\",\"key_constraints\":\"The roof's ability to support the proposed system has not been assessed, and the site's permitted inverter capacity and export limit are unconfirmed. The stated daytime demand range alone does not resolve whether the system can operate within the eventual interconnection conditions.\",\"project_context\":\"A metalworking plant is considering a 300 kWp rooftop PV system. The roof has 2,100 m² of area available after access routes and rooftop equipment are excluded, and the proposed layout avoids a section reported to receive afternoon shade. The plant's weekday daytime demand ranges from 240 to 380 kW. No structural capacity assessment or roof load rating has been provided. The utility has not yet confirmed the permitted inverter capacity or export limit for this site. No project-specific interconnection approval has been issued.\",\"reasoning_answer\":\"There is not enough information to determine feasibility. The available roof area and the identified shading exclusion provide some layout context, but no structural assessment or roof load rating is available to establish whether the roof can support the array. The utility's inverter and export limits are also unknown, and no site-specific interconnection approval has been issued. The next decision inputs are a structural assessment for the proposed system and confirmation of the site's allowable interconnection and export conditions. The stated demand range is not sufficient to resolve those missing constraints.\",\"feasibility_verdict\":\"Insufficient information\"}","MOBIUSI INC","https:\u002F\u002Fstatic.mobiusi.com\u002Fmobiwusi\u002F20250829\u002F7bf4ac62b4533e2b809998a6f1c5491e.png?Expires=1792463130&OSSAccessKeyId=LTAI5tH8MQqhgeiAtrzCHrxM&Signature=v6Tr8jBrdm4s5wU1SnnyGsYg%2Bhw%3D&x-oss-process=image%2Fresize%2Cm_fill%2Cw_35%2Ch_35",[664,670],{"type":665,"title":666,"count_data":667},"bar","Length distribution",[668],{"name":669,"value":483},"1k lower",{"type":671,"title":672,"count_data":673},"pie","Language distribution",[674],{"name":675,"value":483},"English"]