Restrictions, Challenges and Opportunities for AI and ML

Artificial intelligence (AI) refers to a collection of techniques that are being developed to address a wide variety of practical problems. Machine learning (ML) is the backbone of artificial intelligence (AI), comprising a suite of algorithms and techniques designed to solve the issues of categorization, clustering, and prediction. There are bright prospects for putting AI and ML to use in the real world. As a result, there is a lot of study being done in this field. However, mainstream adoption of AI in industry and its widespread use in society are still in their infancy. For understanding the obstacles involved with mainstream AI implementations, both the AI (internal problems) and societal (external problems) viewpoints are required. With this in mind, we can determine what has to happen first to get AI technology into the hands of industry and the public. This article identifies and discusses some of the obstacles to using artificial intelligence in resource-based economies and societies. Publications in the field form the basis for the systematic application of AI&ML technology. This methodical approach makes it possible to define institutional, human resource, societal, and technological constraints. This paper provides a roadmap for future research in artificial intelligence and machine learning that will help us overcome current obstacles and broaden the range of these technologies' potential uses

Restrictions, Challenges and Opportunities for AI and ML

Artificial intelligence (AI) refers to a collection of techniques that are being developed to address a wide variety of practical problems. Machine learning (ML) is the backbone of artificial intelligence (AI), comprising a suite of algorithms and techniques designed to solve the issues of categorization, clustering, and prediction. There are bright prospects for putting AI and ML to use in the real world. As a result, there is a lot of study being done in this field. However, mainstream adoption of AI in industry and its widespread use in society are still in their infancy. For understanding the obstacles involved with mainstream AI implementations, both the AI (internal problems) and societal (external problems) viewpoints are required. With this in mind, we can determine what has to happen first to get AI technology into the hands of industry and the public. This article identifies and discusses some of the obstacles to using artificial intelligence in resource-based economies and societies. Publications in the field form the basis for the systematic application of AI&ML technology. This methodical approach makes it possible to define institutional, human resource, societal, and technological constraints. This paper provides a roadmap for future research in artificial intelligence and machine learning that will help us overcome current obstacles and broaden the range of these technologies' potential uses

Impact Assessment of Commercialization of Main Roads in Planned Housing Schemes: A Case Study of PIA Housing Scheme

The phenomenon of commercialization of residential properties is taking place rapidly. Although conversion of landuse from residential to commercial in built-up areas is not new in developing countries but planned housing schemes also start experiencing this land-use conversion, and now are no more predominantly residential. Furthermore, declaring a road commercial by the competent authorities, even without taking necessary improvements in infrastructure and consent of the community, further exaggerate the problem.  The negative consequences of this phenomenon have a severe effects on residential areas and include environmental problems, traffic congestion, noise, and air pollution, and affect the residential character of the area in negative manner for which they were initially developed. The aim of the study is to describe briefly about remits of commercialization polices in Lahore and then to assess the functionality of commercialized residential roads through assessment criteria based upon the indicators established to assess capacity of road infrastructure before declaring it commercial. This includes road management plan, details of road network with condition of road, its width, Pedestrian and Public transport facilities, structure, including the primary, mixed-use, and secondary nodes. Perception of the users and residents regarding the change in the use of land is also weighed up. The findings of this research will draw the attention of responsible authorities to improve the design guidelines, which are essential to consider before commercializing the residential roads

Impact Assessment of Commercialization of Main Roads in Planned Housing Schemes: A Case Study of PIA Housing Scheme

The phenomenon of commercialization of residential properties is taking place rapidly. Although conversion of landuse from residential to commercial in built-up areas is not new in developing countries but planned housing schemes also start experiencing this land-use conversion, and now are no more predominantly residential. Furthermore, declaring a road commercial by the competent authorities, even without taking necessary improvements in infrastructure and consent of the community, further exaggerate the problem.  The negative consequences of this phenomenon have a severe effects on residential areas and include environmental problems, traffic congestion, noise, and air pollution, and affect the residential character of the area in negative manner for which they were initially developed. The aim of the study is to describe briefly about remits of commercialization polices in Lahore and then to assess the functionality of commercialized residential roads through assessment criteria based upon the indicators established to assess capacity of road infrastructure before declaring it commercial. This includes road management plan, details of road network with condition of road, its width, Pedestrian and Public transport facilities, structure, including the primary, mixed-use, and secondary nodes. Perception of the users and residents regarding the change in the use of land is also weighed up. The findings of this research will draw the attention of responsible authorities to improve the design guidelines, which are essential to consider before commercializing the residential roads

Determination and Mitigation of Urban Heat Island (UHI) In Lahore (A comparative Study of Landsat 8&9)

The term "Urban Heat Island" (UHI) refers to a city or metropolitan area that is significantly warmer than its surroundings. Heatwaves are one of the most visible hazards associated with UHI, that intensified exponentially over the last two decades. The overall approach of the study is initially based on a review of the literature and qualitative studies. The findings were applied to the case study to obtain empirical shreds of evidence. The study investigated the spatiotemporal urbanization trends and their impacts on UHI in Lahore, Pakistan, using multiple datasets. By identifying thermal drivers and simulating the spatial pattern, the direct relationship between development patterns and thermal properties can be visualized. To identify hot spots multi-temporal Landsat TM/OLI satellite images were processed using GIS and remote sensing techniques. It also investigates urban green spaces using spectral indices like the Normalized Difference Vegetation Index (NDVI). The findings indicate that Lahore's urbanization trend is intensifying in both existing and newly proposed zones which increases the pressure on land use planning. The negative correlation between Land Surface Temperature (LST) and NDVI confirms urban sprawl at the expense of green spaces, reshaping and aggregating the UHI profile of Lahore. These methodologies were combined to create UHI mitigation strategies that may aid communication among various stakeholders, including those in academia, development authorities, planners, and practitioners of the built environment. LST calculation by Landsat 9 proved efficient in comparison to Landsat 8 whch may be due to improvement in spatial and spectral domain in architectural design Landsat series.

Riverbank Erosion & Consequent Land Settlement Issues: A Case of River Chenab, District Hafizabad

When calamity strikes, it causes damage but it also provides opportunities for newer learnings opportunities and better preparedness to combat menace. Pakistan is agrarian economy and comprises fertile plains. According to Pakistan Bureau of Statistics, agriculture contributes to 24 percent of national Gross Domestic Product. Agriculture is dependent on water needs, met through water channels fed by rivers originating mostly from glacial sources existing in northern part of the country. The country hosts five major rivers, namely Indus Jhelum, Chenab, Ravi, and Sutlej. The dendritic river patterns follow gravity flow causing frequent morphological changes and riverbank erosion is the most significant phenomenon which acts as hazard for farming communities in terms of loss of shelter, livelihood, and landholdings. An in-time identification of the issue is the real concern nowadays. Presently, different tools are available for instant interpretation of riverbank erosion like Remote Sensing (RS) and Geographical Information System (GIS), which are not only good for instant identification but also helpful for precise estimation of historical losses. Landsat images for years 2009, 2013, and 2017 have used to make an initial assessment of erosion hotspots. High-resolution satellite imagery from Google Earth is also used for meticulous analysis. The analysis shows that beyond other factors, average riverbank displacement rate due to erosion directly depends on rise in water levels. The study provides systematic bases to estimate the losses precisely. The study is useful for damages assessment of land and livelihood to device relief packages for the affected communities. The study also builds the capacity in resolving land settlement issues consequent to the riverbank erosion phenomenon. Full Tex

Riverbank Erosion & Consequent Land Settlement Issues: A Case of River Chenab, District Hafizabad

When calamity strikes, it causes damage but it also provides opportunities for newer learnings opportunities and better preparedness to combat menace. Pakistan is agrarian economy and comprises fertile plains. According to Pakistan Bureau of Statistics, agriculture contributes to 24 percent of national Gross Domestic Product. Agriculture is dependent on water needs, met through water channels fed by rivers originating mostly from glacial sources existing in northern part of the country. The country hosts five major rivers, namely Indus Jhelum, Chenab, Ravi, and Sutlej. The dendritic river patterns follow gravity flow causing frequent morphological changes and riverbank erosion is the most significant phenomenon which acts as hazard for farming communities in terms of loss of shelter, livelihood, and landholdings. An in-time identification of the issue is the real concern nowadays. Presently, different tools are available for instant interpretation of riverbank erosion like Remote Sensing (RS) and Geographical Information System (GIS), which are not only good for instant identification but also helpful for precise estimation of historical losses. Landsat images for years 2009, 2013, and 2017 have used to make an initial assessment of erosion hotspots. High-resolution satellite imagery from Google Earth is also used for meticulous analysis. The analysis shows that beyond other factors, average riverbank displacement rate due to erosion directly depends on rise in water levels. The study provides systematic bases to estimate the losses precisely. The study is useful for damages assessment of land and livelihood to device relief packages for the affected communities. The study also builds the capacity in resolving land settlement issues consequent to the riverbank erosion phenomenon. Full Tex

Determination and Mitigation of Urban Heat Island (UHI) In Lahore (A comparative Study of Landsat 8&9)

The term "Urban Heat Island" (UHI) refers to a city or metropolitan area that is significantly warmer than its surroundings. Heatwaves are one of the most visible hazards associated with UHI, that intensified exponentially over the last two decades. The overall approach of the study is initially based on a review of the literature and qualitative studies. The findings were applied to the case study to obtain empirical shreds of evidence. The study investigated the spatiotemporal urbanization trends and their impacts on UHI in Lahore, Pakistan, using multiple datasets. By identifying thermal drivers and simulating the spatial pattern, the direct relationship between development patterns and thermal properties can be visualized. To identify hot spots multi-temporal Landsat TM/OLI satellite images were processed using GIS and remote sensing techniques. It also investigates urban green spaces using spectral indices like the Normalized Difference Vegetation Index (NDVI). The findings indicate that Lahore's urbanization trend is intensifying in both existing and newly proposed zones which increases the pressure on land use planning. The negative correlation between Land Surface Temperature (LST) and NDVI confirms urban sprawl at the expense of green spaces, reshaping and aggregating the UHI profile of Lahore. These methodologies were combined to create UHI mitigation strategies that may aid communication among various stakeholders, including those in academia, development authorities, planners, and practitioners of the built environment. LST calculation by Landsat 9 proved efficient in comparison to Landsat 8 whch may be due to improvement in spatial and spectral domain in architectural design Landsat series.