AFFECTIVE-FUNCTIONAL-MORPHOLOGICAL TRIPARTITE MAPPING: A KANSEI ENGINEERING STUDY OF POLICE DRONES

Authors

  • Zhe Liu Doctoral Student of Philosophy Program in Visual Arts and Design, Faculty of Fine and Applied Arts, Suan Sunandha Rajabhat University, Thailand
  • Chanoknart Mayusoh Advisor in Visual Arts and Design, Faculty of Fine and Applied Arts, Suan Sunandha Rajabhat University, Thailand
  • Akapong Inkuer Visual Arts and Design, Faculty of Fine and Applied Arts, Suan Sunandha Rajabhat University, Thailand
  • Permsak Suwannatat Program in Creative Arts Department, Faculty of Fine and Applied Arts Chulalongkorn University, Thailand

DOI:

https://doi.org/10.29121/shodhkosh.v7.i1.2026.7854

Keywords:

Police Drone, Kansei Engineering, Value Sensitive Design (Vsd), Affective Semantics, Design Framework

Abstract [English]

A techno-semantic imbalance is prevalent in current police drones, stemming from a structural decoupling between their functional platform and symbolic form. When consumer-grade drones are retrofitted for police missions, their design semantics fail to effectively encode "law enforcement authority". This leads to the diminished efficacy of what Bourdieu termed "symbolic violence", Bourdieu (1991) causing a systemic loss of symbolic deterrence. The cognitive paradox between this "residual civilian DNA" and the "deterrent signifier" required by police work is the core design challenge to be solved. Guided by Value-Sensitive Design (VSD) principles, this study constructs an integrated Kansei Engineering framework to balance the tripartite needs of law enforcement authority, public sense of security, and psychological deterrence. The study builds and validates this framework through a three-stage "Emotion-Function-Form" mapping mechanism. First, the Kano model is used to analyze the non-linear structure of users' affective needs, identifying emotional-layer requirements. Second, a Quality Function Deployment (QFD) matrix translates these abstract affective demands into functional-layer engineering design elements. Finally, the Semantic Differential (SD) method provides closed-loop validation by assessing the semantic effectiveness of the resulting design form. Empirical results demonstrate the framework's validity. The Kano analysis identifies "a bionic form with dynamic tension" as a key attractive attribute (Better coefficient = 0.69). In the SD evaluation, the prototype demonstrated significant differences from commercial drones on the metrics of "authoritativeness" and "professionalism," while keeping "threat perception" within a preset threshold, thus precisely calibrating the semantic boundaries. This research proposes and substantiates an "Emotion-Function-Form Triadic Mapping Model." Through its three-stage Kano-QFD-SD mechanism, it offers a systematic paradigm for designing professional equipment with high perceptual impact. Furthermore, it provides an operational pathway for translating abstract ethical principles, such as "minimum necessary deterrence," into quantifiable engineering constraints, offering significant methodological implications for responsible technological innovation.

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Published

2026-05-07

How to Cite

Liu , Z., Mayusoh, C., Inkuer, A., & Suwannatat, P. (2026). AFFECTIVE-FUNCTIONAL-MORPHOLOGICAL TRIPARTITE MAPPING: A KANSEI ENGINEERING STUDY OF POLICE DRONES. ShodhKosh: Journal of Visual and Performing Arts, 7(1), 544–555. https://doi.org/10.29121/shodhkosh.v7.i1.2026.7854